Job Details Salary: Competitive Plus Benefits Location: London Store Support Centre, London, EC1M 6HA Contract type: Permanent Business area: Sainsbury's Tech Closing date: 29 July 2026 Requisition ID: Job Title Senior Machine Learning Engineer Job Overview As a Senior Machine Learning Engineer, you will play a pivotal role in designing, building, and optimising a Machine Learning system for Advert Classification. We are looking for a leader competent across modern ML tooling, methodologies, and design practices, while also able to design hybrid systems that integrate LLMs. The lead is expected to drive the ML design and build lifecycle, arriving at a reliable and performant system, supporting a team of Data Scientists in delivery. Systematic evaluation of performance with data is a critical part of our ML initiatives; the lead will drive strategy and operationalise automatic machine evaluation with metrics and best practice MLOps. You will partner with Data Scientists and Software Engineers to ensure the system is reliable, performant, and production ready. You will also contribute to engineering excellence across Machine Learning and MLOps by driving best practices, mentoring other engineers, and shaping the technical direction of data and ML workflows across our domain. Key Responsibilities Lead the design and build of high quality, scalable, and reusable Machine Learning systems using Sainsbury's engineering standards and best practices. Design and optimise Machine Learning modules for Advert classification, applying the ML Lifecycle and best practice in model selection and development. Lead the design and implementation of supporting Machine Learning Operations, applying best in class approaches to data versioning, model re training, and data observability. Implement automation tools and frameworks for experiment tracking, data and model observability to streamline deployment and monitoring of machine learning models in production. Lead the system evaluation methodology, including evaluation strategy, data generation, and evaluation metrics. Provide guidance to mid level Data Scientists on best practice and methodological choices when optimising machine learning modules and the system overall; offer technical guidance on emerging technologies in data engineering and machine learning to enhance their skills and career growth. Collaborate and support with data scientists across the lifecycle, including EDA, data transformation, model selection, feature engineering, and model selection. Optimise data processing workflows and storage solutions to improve performance and reduce costs. Work closely with cross functional teams, including software engineering and product management, to deliver data solutions that meet business needs. Promote a culture of knowledge sharing within the engineering teams by organising regular technical workshops, brown bag sessions, and code reviews. Encourage continuous learning and improvement, fostering a collaborative and inclusive team environment. Have 6-10 years of experience designing and building Machine Learning systems end to end, including strong experience implementing MLOps. Qualifications Strong understanding of modern Machine Learning methodologies, Data Science, and accompanying algorithms. Good experience integrating LLMs as hybrid AI ML systems. Academic background with at least a BSc in Computer Science. Experience in modern Computer Vision, having built image detection systems end to end. Strong understanding of ML deployment and management on modern Cloud platforms, specifically MS Azure and AWS. Strong analytical and problem solving skills. Excellent communication skills, able to explain complex concepts to non technical stakeholders. Ability to work independently as well as collaboratively within cross functional teams. Leadership and Communication Provide technical direction, set standards, and lead by example in science and engineering excellence. Facilitate Scrum ceremonies when required (stand ups, planning, grooming). Communicate clearly and transparently, creating an inclusive environment where diverse opinions are encouraged. Strong team player with a collaborative approach to working with cross functional teams within the Media Agency. Open to feedback and willing to provide constructive criticism to others. Be available for the team, responding within a reasonable time frame, and if not possible, clearly signpost alternative contacts who can guide. Build a community across the Media Agency. Contribute to a positive and inclusive atmosphere within the team. Knowledge Sharing and Empowerment Commitment to fostering a learning culture within the team and ensuring knowledge transfer across all levels. Support and mentor C3s and C4s engineers by providing them opportunities to lead initiatives and contribute to the technical roadmap. Deliver Through Others Share domain expertise proactively and help establish the engineering direction for the team. Support spikes, POCs and early investigative work. Lead by example in communication, visibility, accountability and role modeling Sainsbury's values. Benefits Starting off with colleague discount, you will be able to get 10% off at Sainsbury's, Argos, TU and Habitat after 4 weeks. This increases to 15% off at Sainsbury's every Friday and Saturday and 15% off at Argos every pay day. We also have pensions scheme and life cover, and you may be eligible for a performance related bonus of up to 20% of salary, depending on how we perform. Your wellbeing is important to us too. You will receive an annual holiday allowance, and you can buy additional holiday. We also offer other benefits that will help your money go further such as season ticket loans, interest free car loan of up to £10k, cycle to work scheme, health cash plans, pay advance, and access to a great range of discounts from hundreds of other retailers. There is also an Employee Assistance Programme, and you will be eligible for private healthcare. We provide up to 26 weeks' pay for maternity or adoption leave and up to 4 weeks' pay for paternity leave.
25/07/2026
Full time
Job Details Salary: Competitive Plus Benefits Location: London Store Support Centre, London, EC1M 6HA Contract type: Permanent Business area: Sainsbury's Tech Closing date: 29 July 2026 Requisition ID: Job Title Senior Machine Learning Engineer Job Overview As a Senior Machine Learning Engineer, you will play a pivotal role in designing, building, and optimising a Machine Learning system for Advert Classification. We are looking for a leader competent across modern ML tooling, methodologies, and design practices, while also able to design hybrid systems that integrate LLMs. The lead is expected to drive the ML design and build lifecycle, arriving at a reliable and performant system, supporting a team of Data Scientists in delivery. Systematic evaluation of performance with data is a critical part of our ML initiatives; the lead will drive strategy and operationalise automatic machine evaluation with metrics and best practice MLOps. You will partner with Data Scientists and Software Engineers to ensure the system is reliable, performant, and production ready. You will also contribute to engineering excellence across Machine Learning and MLOps by driving best practices, mentoring other engineers, and shaping the technical direction of data and ML workflows across our domain. Key Responsibilities Lead the design and build of high quality, scalable, and reusable Machine Learning systems using Sainsbury's engineering standards and best practices. Design and optimise Machine Learning modules for Advert classification, applying the ML Lifecycle and best practice in model selection and development. Lead the design and implementation of supporting Machine Learning Operations, applying best in class approaches to data versioning, model re training, and data observability. Implement automation tools and frameworks for experiment tracking, data and model observability to streamline deployment and monitoring of machine learning models in production. Lead the system evaluation methodology, including evaluation strategy, data generation, and evaluation metrics. Provide guidance to mid level Data Scientists on best practice and methodological choices when optimising machine learning modules and the system overall; offer technical guidance on emerging technologies in data engineering and machine learning to enhance their skills and career growth. Collaborate and support with data scientists across the lifecycle, including EDA, data transformation, model selection, feature engineering, and model selection. Optimise data processing workflows and storage solutions to improve performance and reduce costs. Work closely with cross functional teams, including software engineering and product management, to deliver data solutions that meet business needs. Promote a culture of knowledge sharing within the engineering teams by organising regular technical workshops, brown bag sessions, and code reviews. Encourage continuous learning and improvement, fostering a collaborative and inclusive team environment. Have 6-10 years of experience designing and building Machine Learning systems end to end, including strong experience implementing MLOps. Qualifications Strong understanding of modern Machine Learning methodologies, Data Science, and accompanying algorithms. Good experience integrating LLMs as hybrid AI ML systems. Academic background with at least a BSc in Computer Science. Experience in modern Computer Vision, having built image detection systems end to end. Strong understanding of ML deployment and management on modern Cloud platforms, specifically MS Azure and AWS. Strong analytical and problem solving skills. Excellent communication skills, able to explain complex concepts to non technical stakeholders. Ability to work independently as well as collaboratively within cross functional teams. Leadership and Communication Provide technical direction, set standards, and lead by example in science and engineering excellence. Facilitate Scrum ceremonies when required (stand ups, planning, grooming). Communicate clearly and transparently, creating an inclusive environment where diverse opinions are encouraged. Strong team player with a collaborative approach to working with cross functional teams within the Media Agency. Open to feedback and willing to provide constructive criticism to others. Be available for the team, responding within a reasonable time frame, and if not possible, clearly signpost alternative contacts who can guide. Build a community across the Media Agency. Contribute to a positive and inclusive atmosphere within the team. Knowledge Sharing and Empowerment Commitment to fostering a learning culture within the team and ensuring knowledge transfer across all levels. Support and mentor C3s and C4s engineers by providing them opportunities to lead initiatives and contribute to the technical roadmap. Deliver Through Others Share domain expertise proactively and help establish the engineering direction for the team. Support spikes, POCs and early investigative work. Lead by example in communication, visibility, accountability and role modeling Sainsbury's values. Benefits Starting off with colleague discount, you will be able to get 10% off at Sainsbury's, Argos, TU and Habitat after 4 weeks. This increases to 15% off at Sainsbury's every Friday and Saturday and 15% off at Argos every pay day. We also have pensions scheme and life cover, and you may be eligible for a performance related bonus of up to 20% of salary, depending on how we perform. Your wellbeing is important to us too. You will receive an annual holiday allowance, and you can buy additional holiday. We also offer other benefits that will help your money go further such as season ticket loans, interest free car loan of up to £10k, cycle to work scheme, health cash plans, pay advance, and access to a great range of discounts from hundreds of other retailers. There is also an Employee Assistance Programme, and you will be eligible for private healthcare. We provide up to 26 weeks' pay for maternity or adoption leave and up to 4 weeks' pay for paternity leave.
We'd all like amazing work to do, and real work life balance. That's waiting for you at Sainsbury's. Think about the scale it takes to feed the nation. The level of data, transactions and variety involved. Then you'll realise this is a modern software engineering environment, because it has to be. We've made significant investment in the standards and principles that shape how we work. We iterate, learn, experiment and champion ways of working such as Agile, Scrum and XP. So you can look forward to exciting opportunities across everything from AI to reusable tech. Job Title: Senior Machine Learning Engineer Location: London Department: Media Agency Job Overview As a Senior Machine Learning Engineer, you will play a pivotal role in designing, building and optimising a Machine Learning system for Advert Classification. We are looking for a Machine Learning leader who is competent across modern ML tooling, methodologies and design practices, whilst also being able to design hybrid systems that integrate LLMs. The Machine Learning lead is expected to lead the ML design and build lifecycle, arriving at a reliable and performant system, supporting a team of Data Scientists in the delivery. Systematic evaluation of performance with data is a critical part of our ML initiatives and as a result the ML Lead is expected to drive the strategy and operationalise automatic machine evaluation with metrics and best practice MLOps. You will partner with Data Scientists and Software Engineers, to ensure the system is reliable, performant and production ready. You will also contribute to engineering excellence, across Machine Learning and MLOps, by driving best practices, mentoring other engineers, and shaping the technical direction of data and ML workflows across our domain. Key Responsibilities Lead the design and build of high quality, scalable and reusable Machine Learning systems using Sainsbury's engineering standards and best practices. Design and optimise Machine Learning modules for Advert classification, applying the ML Lifecycle and best practice in model selection and development. Lead the design and implementation of supporting Machine Learning Operations, applying best in class approaches to data versions, model re training and data observability. Implement automation tools and frameworks for experiment tracking, data and model observability to streamline the deployment and monitoring of machine learning models in production. Lead the system evaluation methodology, including the evaluation strategy, data generation and evaluation metrics. Provide guidance to mid Data Scientists on best practice and methodological choices, when optimising machine learning modules and the system, overall. Provide technical guidance on best practices and emerging technologies in data engineering and machine learning and helping to enhance their skills and career growth. Collaborate and support with data scientists across the lifecycle, including EDA, data transformation, model selection, feature engineering, model selection. Optimise data processing workflows and storage solutions to improve performance and reduce costs. Work closely with cross functional teams, including software engineering and product management, to deliver data solutions that meet business needs. Promote a culture of knowledge sharing within the engineering teams by organising regular technical workshops, brown bag sessions, and code reviews. Innovation and Continuous Improvement: Foster a collaborative and inclusive team environment that encourages continuous learning and improvement. Essential Criteria 6-10 years experience designing and building Machine Learning systems end to end, including strong experience implementing MLOps. Strong understanding of modern Machine Learning methodologies, Data Science and accompanying algorithms. Additionally, good experience integrating LLMs as hybrid AI ML systems. Academic background with at least a BSc in Computer Science. Desirable Criteria Experience in modern Computer Vision, having built image detection systems end to end. Strong understanding of ML deployment and management on modern Cloud platforms, specifically MS Azure and AWS. Strong analytical and problem solving skills. Excellent communication skills, able to explain complex concepts to non technical stakeholders. Ability to work independently as well as collaboratively within cross functional teams. Expectations Leadership and Communication Provide technical direction, set standards, and lead by example in science and engineering excellence. Facilitate Scrum ceremonies when required (stand ups, planning, grooming). Communicate clearly and transparently, creating an inclusive environment where diverse opinions are encouraged. Collaborative Attitude Strong team player with a collaborative approach to working with cross functional teams within the Media Agency. Open to feedback and willing to provide constructive criticism to others. Be available for the team, responding within a reasonable time frame and if not possible clearly signpost alternative contacts who can guide. Building a community across Media Agency. Contribute to a positive and inclusive atmosphere within the team. Knowledge Sharing and Empowerment Commitment to fostering a learning culture within the team and ensuring knowledge transfer across all levels. Support and mentor C3s and C4s engineers by providing them opportunities to lead initiatives and contribute to the technical roadmap. Deliver Through Others Share domain expertise proactively and help establish the engineering direction for the team. Support spikes, POCs and early investigative work. Encourage strong developer behaviors (e.g., cameras on for collaboration, documentation, active presence). Lead by example in communication, visibility, accountability and role modeling Sainsbury's values. "We are committed to being a truly inclusive retailer, so you'll be welcomed whoever you are and wherever you work. Around here, there's always the chance to try something new - whether that's as part of an evolving team or somewhere else across the business - and we take development seriously and promise to support you. We also recognise and celebrate colleagues when they go the extra mile and, where possible, offer flexible working. When you join our team, we'll also offer you an amazing range of benefits. Here are some of them: Starting off with colleague discount, you'll be able to get 10% off at Sainsbury's, Argos, TU and Habitat after 4 weeks. This increases to 15% off at Sainsbury's every Friday and Saturday and 15% off at Argos every pay day. We've also got you covered for your future with our pensions scheme and life cover. You'll also be able to share in our success as you may be eligible for a performance related bonus of up to 20% of salary, depending on how we perform. Your wellbeing is important to us too. You'll receive an annual holiday allowance, and you can buy additional holiday. We also offer other benefits that will help your money go further such as season ticket loans, interest free car loan of up to £10k, cycle to work scheme, health cash plans, pay advance (where you can access some of your pay before pay day) as well access to a great range of discounts from hundreds of other retailers. And if you ever need it there is also an Employee Assistance Programme, you will also be eligible for private healthcare too. Moments that matter are as important to us as they are to you which is why we give up to 26 weeks' pay for maternity or adoption leave and up to 4 weeks' pay for paternity leave. Please see for a range of our benefits (note, length of service and eligibility criteria may apply)."
24/07/2026
Full time
We'd all like amazing work to do, and real work life balance. That's waiting for you at Sainsbury's. Think about the scale it takes to feed the nation. The level of data, transactions and variety involved. Then you'll realise this is a modern software engineering environment, because it has to be. We've made significant investment in the standards and principles that shape how we work. We iterate, learn, experiment and champion ways of working such as Agile, Scrum and XP. So you can look forward to exciting opportunities across everything from AI to reusable tech. Job Title: Senior Machine Learning Engineer Location: London Department: Media Agency Job Overview As a Senior Machine Learning Engineer, you will play a pivotal role in designing, building and optimising a Machine Learning system for Advert Classification. We are looking for a Machine Learning leader who is competent across modern ML tooling, methodologies and design practices, whilst also being able to design hybrid systems that integrate LLMs. The Machine Learning lead is expected to lead the ML design and build lifecycle, arriving at a reliable and performant system, supporting a team of Data Scientists in the delivery. Systematic evaluation of performance with data is a critical part of our ML initiatives and as a result the ML Lead is expected to drive the strategy and operationalise automatic machine evaluation with metrics and best practice MLOps. You will partner with Data Scientists and Software Engineers, to ensure the system is reliable, performant and production ready. You will also contribute to engineering excellence, across Machine Learning and MLOps, by driving best practices, mentoring other engineers, and shaping the technical direction of data and ML workflows across our domain. Key Responsibilities Lead the design and build of high quality, scalable and reusable Machine Learning systems using Sainsbury's engineering standards and best practices. Design and optimise Machine Learning modules for Advert classification, applying the ML Lifecycle and best practice in model selection and development. Lead the design and implementation of supporting Machine Learning Operations, applying best in class approaches to data versions, model re training and data observability. Implement automation tools and frameworks for experiment tracking, data and model observability to streamline the deployment and monitoring of machine learning models in production. Lead the system evaluation methodology, including the evaluation strategy, data generation and evaluation metrics. Provide guidance to mid Data Scientists on best practice and methodological choices, when optimising machine learning modules and the system, overall. Provide technical guidance on best practices and emerging technologies in data engineering and machine learning and helping to enhance their skills and career growth. Collaborate and support with data scientists across the lifecycle, including EDA, data transformation, model selection, feature engineering, model selection. Optimise data processing workflows and storage solutions to improve performance and reduce costs. Work closely with cross functional teams, including software engineering and product management, to deliver data solutions that meet business needs. Promote a culture of knowledge sharing within the engineering teams by organising regular technical workshops, brown bag sessions, and code reviews. Innovation and Continuous Improvement: Foster a collaborative and inclusive team environment that encourages continuous learning and improvement. Essential Criteria 6-10 years experience designing and building Machine Learning systems end to end, including strong experience implementing MLOps. Strong understanding of modern Machine Learning methodologies, Data Science and accompanying algorithms. Additionally, good experience integrating LLMs as hybrid AI ML systems. Academic background with at least a BSc in Computer Science. Desirable Criteria Experience in modern Computer Vision, having built image detection systems end to end. Strong understanding of ML deployment and management on modern Cloud platforms, specifically MS Azure and AWS. Strong analytical and problem solving skills. Excellent communication skills, able to explain complex concepts to non technical stakeholders. Ability to work independently as well as collaboratively within cross functional teams. Expectations Leadership and Communication Provide technical direction, set standards, and lead by example in science and engineering excellence. Facilitate Scrum ceremonies when required (stand ups, planning, grooming). Communicate clearly and transparently, creating an inclusive environment where diverse opinions are encouraged. Collaborative Attitude Strong team player with a collaborative approach to working with cross functional teams within the Media Agency. Open to feedback and willing to provide constructive criticism to others. Be available for the team, responding within a reasonable time frame and if not possible clearly signpost alternative contacts who can guide. Building a community across Media Agency. Contribute to a positive and inclusive atmosphere within the team. Knowledge Sharing and Empowerment Commitment to fostering a learning culture within the team and ensuring knowledge transfer across all levels. Support and mentor C3s and C4s engineers by providing them opportunities to lead initiatives and contribute to the technical roadmap. Deliver Through Others Share domain expertise proactively and help establish the engineering direction for the team. Support spikes, POCs and early investigative work. Encourage strong developer behaviors (e.g., cameras on for collaboration, documentation, active presence). Lead by example in communication, visibility, accountability and role modeling Sainsbury's values. "We are committed to being a truly inclusive retailer, so you'll be welcomed whoever you are and wherever you work. Around here, there's always the chance to try something new - whether that's as part of an evolving team or somewhere else across the business - and we take development seriously and promise to support you. We also recognise and celebrate colleagues when they go the extra mile and, where possible, offer flexible working. When you join our team, we'll also offer you an amazing range of benefits. Here are some of them: Starting off with colleague discount, you'll be able to get 10% off at Sainsbury's, Argos, TU and Habitat after 4 weeks. This increases to 15% off at Sainsbury's every Friday and Saturday and 15% off at Argos every pay day. We've also got you covered for your future with our pensions scheme and life cover. You'll also be able to share in our success as you may be eligible for a performance related bonus of up to 20% of salary, depending on how we perform. Your wellbeing is important to us too. You'll receive an annual holiday allowance, and you can buy additional holiday. We also offer other benefits that will help your money go further such as season ticket loans, interest free car loan of up to £10k, cycle to work scheme, health cash plans, pay advance (where you can access some of your pay before pay day) as well access to a great range of discounts from hundreds of other retailers. And if you ever need it there is also an Employee Assistance Programme, you will also be eligible for private healthcare too. Moments that matter are as important to us as they are to you which is why we give up to 26 weeks' pay for maternity or adoption leave and up to 4 weeks' pay for paternity leave. Please see for a range of our benefits (note, length of service and eligibility criteria may apply)."
Location: Hybrid / Monument St, London EC3R 8AJ, UK job type: Permanent / Full-time Sector and subsector: IT Data Science Salary: Negotiable salary As a Data Scientist within the Analytics Team, you will contribute to data-driven strategies for our clients. Working closely with the Data & Analytics Manager and senior colleagues, you will deliver data science projects and collaborate with stakeholders across data strategy, sales, account management, delivery and marketing. You will bring solid technical skills and commercial awareness to deliver data solutions that drive measurable operational performance. This is a hands on role - ideal for someone who thrives on translating data into actionable insight and producing high quality outcomes. Responsibilities Deliver data science projects, from problem definition through to actionable insights and presentation of results Develop and apply predictive modelling, supervised and unsupervised machine learning techniques to optimise client operations and business outcomes Build and maintain data pipelines, ensuring data quality, consistency, and integrity across multiple sources and formats Translate complex analyses into clear, commercially relevant recommendations for clients and internal stakeholders Work with client teams to identify analytical opportunities, support marketing strategy, and quantify the impact of data-driven decision-making Support pre sales and client engagement, helping to demonstrate the value of data insight Follow best practices in data science, reproducible research, and ethical AI Collaborate cross functionally to enhance the company's products and marketing data solutions What Success Looks Like in the Role Delivery of impactful, high-quality analytics that directly inform and improve client marketing outcomes Building trust and credibility with clients as an analytical consultant Regular iteration on our machine learning methodologies, tools, and frameworks Consistent demonstration of technical excellence and commercial insight in all project deliverables Measurable contribution to the enhancement of Sagacity's data science and analytics product suite Competencies and Experience 2+ years' experience in data science, analytics, or statistical modelling, ideally with commercial experience within the Telecoms, Banking or Utilities industries; or within a data related consultancy Educated to degree level (postgraduate preferred) in a quantitative discipline such as Computer Science, Statistics, Mathematics, Economics, or similar Working knowledge of statistical and machine learning methods (e.g. logistic regression, gradient boosting, random forests, clustering, NLP Proficient in Python and/or R, with strong experience in data quality, model development and feature engineering Strong command of SQL and familiarity with data engineering environments such as Databricks or similar Skilled in data visualisation and storytelling using tools such as Power BI, Tableau, Plotly, or Sigma Demonstrated ability to translate technical findings into strategic recommendations for non technical audiences Commercially aware, with proven success in applying analytics to solve business problems Strong communicator; able to engage stakeholders and present findings with clarity and confidence Self motivated, organised, and proactive, with the ability to manage multiple priorities and stakeholders in a fast paced environment Willing to travel across the UK for client engagements Must have the right to work in the UK and a commitment to ongoing professional development
18/07/2026
Full time
Location: Hybrid / Monument St, London EC3R 8AJ, UK job type: Permanent / Full-time Sector and subsector: IT Data Science Salary: Negotiable salary As a Data Scientist within the Analytics Team, you will contribute to data-driven strategies for our clients. Working closely with the Data & Analytics Manager and senior colleagues, you will deliver data science projects and collaborate with stakeholders across data strategy, sales, account management, delivery and marketing. You will bring solid technical skills and commercial awareness to deliver data solutions that drive measurable operational performance. This is a hands on role - ideal for someone who thrives on translating data into actionable insight and producing high quality outcomes. Responsibilities Deliver data science projects, from problem definition through to actionable insights and presentation of results Develop and apply predictive modelling, supervised and unsupervised machine learning techniques to optimise client operations and business outcomes Build and maintain data pipelines, ensuring data quality, consistency, and integrity across multiple sources and formats Translate complex analyses into clear, commercially relevant recommendations for clients and internal stakeholders Work with client teams to identify analytical opportunities, support marketing strategy, and quantify the impact of data-driven decision-making Support pre sales and client engagement, helping to demonstrate the value of data insight Follow best practices in data science, reproducible research, and ethical AI Collaborate cross functionally to enhance the company's products and marketing data solutions What Success Looks Like in the Role Delivery of impactful, high-quality analytics that directly inform and improve client marketing outcomes Building trust and credibility with clients as an analytical consultant Regular iteration on our machine learning methodologies, tools, and frameworks Consistent demonstration of technical excellence and commercial insight in all project deliverables Measurable contribution to the enhancement of Sagacity's data science and analytics product suite Competencies and Experience 2+ years' experience in data science, analytics, or statistical modelling, ideally with commercial experience within the Telecoms, Banking or Utilities industries; or within a data related consultancy Educated to degree level (postgraduate preferred) in a quantitative discipline such as Computer Science, Statistics, Mathematics, Economics, or similar Working knowledge of statistical and machine learning methods (e.g. logistic regression, gradient boosting, random forests, clustering, NLP Proficient in Python and/or R, with strong experience in data quality, model development and feature engineering Strong command of SQL and familiarity with data engineering environments such as Databricks or similar Skilled in data visualisation and storytelling using tools such as Power BI, Tableau, Plotly, or Sigma Demonstrated ability to translate technical findings into strategic recommendations for non technical audiences Commercially aware, with proven success in applying analytics to solve business problems Strong communicator; able to engage stakeholders and present findings with clarity and confidence Self motivated, organised, and proactive, with the ability to manage multiple priorities and stakeholders in a fast paced environment Willing to travel across the UK for client engagements Must have the right to work in the UK and a commitment to ongoing professional development
Project description We are hiring in the Middle East. There are many projects and opportunities in the region. Our team consists of frontend and backend developers, data analysts and data scientists, architects, analysts and project managers. Responsibilities Develop and maintain scalable solutions using Python, PySpark, and SQL. Design and implement data pipelines (ingestion, transformation, modelling, data quality checks, automation). Build and integrate APIs (REST, SOAP, gRPC), including authentication and authorization. Contribute to application architecture design, applying best practices and design patterns. Implement Test-Driven Development (TDD) and ensure high code quality. Support and enhance CI/CD pipelines and DevOps processes. Work with cloud platforms (AWS, Azure) and data platforms such as Databricks and Palantir Foundry. Develop UI components and dashboards using Dash, JavaScript, and React. Integrate with market data and investment platforms. Support quantitative models and analytics (Monte Carlo simulations, pricing, risk, factor modelling). Contribute to portfolio management processes (asset allocation, rebalancing, attribution). Analyze complex datasets and deliver actionable insights for business and investment decisions. Gather and challenge business requirements, define solutions, and report on delivery progress. Collaborate within Agile teams, ensuring effective communication and alignment. Stay updated on emerging technologies and industry trends, proposing improvements. Balance short-term deliverables with long-term architectural goals. SKILLS Must have Python (Advanced), PySpark (Medium), SQL (Advanced) Dash (Python framework), JavaScript (Medium), React (Preferred), OpenFin / FTC3 (Preferred) Azure (Preferred), AWS (Medium) DataBricks (Preferred), Palantir Foundry (Medium) Test-driven Development (Advanced), CICD (Medium), DevOps (Advanced) Application Architecture design and development (Design patterns etc) Data Engineering (Ingestion, Curation, Modelling, Automation, Data Quality Checks) (Preferred) APIs (patterns, authorization, SOAP, REST, GRPC) (Advanced) Data Science (Preferred) Understand and provide insights on emerging industry trends. Domain Knowledge Knowledge / experience in financial markets and alternative asset classes (Hedge Funds) Knowledge / experience in end-to-end portfolio management (asset allocation, portfolio construction, rebalancing, implementation, attribution) Experience with sourcing data from, and integrating with, core investment and/or market data platforms Knowledge / experience with Quant processes (Monte Carlo simulation, pricing engines, optimization techniques, factor modelling, risk) Nice to have Ability to gather requirements, challenge, define structure and report upon status of deliverables. Strong collaboration and team culture, working in Agile delivery. Strong problem-solving skills and ability to effectively resolve issues in a timely manner. Excellent interpersonal skills, including collaboration, facilitation, and negotiation. Excellent written and verbal communication skills. Ability to balance the long-term ("big picture") and short-term implications of individual decisions.
15/07/2026
Full time
Project description We are hiring in the Middle East. There are many projects and opportunities in the region. Our team consists of frontend and backend developers, data analysts and data scientists, architects, analysts and project managers. Responsibilities Develop and maintain scalable solutions using Python, PySpark, and SQL. Design and implement data pipelines (ingestion, transformation, modelling, data quality checks, automation). Build and integrate APIs (REST, SOAP, gRPC), including authentication and authorization. Contribute to application architecture design, applying best practices and design patterns. Implement Test-Driven Development (TDD) and ensure high code quality. Support and enhance CI/CD pipelines and DevOps processes. Work with cloud platforms (AWS, Azure) and data platforms such as Databricks and Palantir Foundry. Develop UI components and dashboards using Dash, JavaScript, and React. Integrate with market data and investment platforms. Support quantitative models and analytics (Monte Carlo simulations, pricing, risk, factor modelling). Contribute to portfolio management processes (asset allocation, rebalancing, attribution). Analyze complex datasets and deliver actionable insights for business and investment decisions. Gather and challenge business requirements, define solutions, and report on delivery progress. Collaborate within Agile teams, ensuring effective communication and alignment. Stay updated on emerging technologies and industry trends, proposing improvements. Balance short-term deliverables with long-term architectural goals. SKILLS Must have Python (Advanced), PySpark (Medium), SQL (Advanced) Dash (Python framework), JavaScript (Medium), React (Preferred), OpenFin / FTC3 (Preferred) Azure (Preferred), AWS (Medium) DataBricks (Preferred), Palantir Foundry (Medium) Test-driven Development (Advanced), CICD (Medium), DevOps (Advanced) Application Architecture design and development (Design patterns etc) Data Engineering (Ingestion, Curation, Modelling, Automation, Data Quality Checks) (Preferred) APIs (patterns, authorization, SOAP, REST, GRPC) (Advanced) Data Science (Preferred) Understand and provide insights on emerging industry trends. Domain Knowledge Knowledge / experience in financial markets and alternative asset classes (Hedge Funds) Knowledge / experience in end-to-end portfolio management (asset allocation, portfolio construction, rebalancing, implementation, attribution) Experience with sourcing data from, and integrating with, core investment and/or market data platforms Knowledge / experience with Quant processes (Monte Carlo simulation, pricing engines, optimization techniques, factor modelling, risk) Nice to have Ability to gather requirements, challenge, define structure and report upon status of deliverables. Strong collaboration and team culture, working in Agile delivery. Strong problem-solving skills and ability to effectively resolve issues in a timely manner. Excellent interpersonal skills, including collaboration, facilitation, and negotiation. Excellent written and verbal communication skills. Ability to balance the long-term ("big picture") and short-term implications of individual decisions.
Data Scientist / Senior Data Scientist London, United Kingdom - Posted 9 months ago. Tech stack Artificial Intelligence Java GitHub JavaScript Preferred Qualifications Experience with JavaScript and Java. Experience with time series and dynamical systems. A portfolio of projects (GitHub, papers, etc.). C3 AI provides excellent verbal and written communication. Ability to travel as needed. C3 AI C3.ai is a leading enterprise AI software provider for building enterprise scale AI applications and accelerating digital transformation. Compensation Competitive. Role type Full time. Visa sponsorship Not provided.
05/07/2026
Full time
Data Scientist / Senior Data Scientist London, United Kingdom - Posted 9 months ago. Tech stack Artificial Intelligence Java GitHub JavaScript Preferred Qualifications Experience with JavaScript and Java. Experience with time series and dynamical systems. A portfolio of projects (GitHub, papers, etc.). C3 AI provides excellent verbal and written communication. Ability to travel as needed. C3 AI C3.ai is a leading enterprise AI software provider for building enterprise scale AI applications and accelerating digital transformation. Compensation Competitive. Role type Full time. Visa sponsorship Not provided.