Datalex
Manchester, Lancashire
Senior Software Engineer - Pricing AI (Manchester) The Role We are seeking a talented Senior Developer with a strong focus on Python-based AI/ML development, automation, and general software engineering. The successful candidate will play a key role in building and deploying machine learning features and data-driven applications. You will work on end-to-end solutions - from writing robust code and unit tests to developing APIs and integrating machine learning models into our product ecosystem. This role requires a mix of software engineering excellence, an eye for automation, and hands on experience with AI/ML frameworks. If you are passionate about leveraging Python to solve complex problems and deliver scalable AI solutions, we want to hear from you. Experience in the travel or retail industry would be an advantage. Responsibilities Design, implement, and maintain software components that incorporate machine learning algorithms and data processing, and develop clean, efficient Python code for both backend logic and integration of ML models. Understand the business drivers behind each feature. Create and optimise data pipelines to collect, preprocess, and transform data for machine learning and analytics; work with large datasets, ensuring data quality and availability for training and prediction tasks. Develop robust RESTful APIs and microservices (using frameworks like FastAPI or Flask) to expose machine learning functionalities and data services; ensure APIs are secure, well documented, and perform at scale. Write and maintain comprehensive tests for your code; use PyTest for unit testing and Selenium (where appropriate) for end to end or UI testing to automate quality assurance; ensure that new features have proper test coverage and meet quality standards before deployment. Collaborate with DevOps engineers to set up and maintain CI/CD pipelines for building, testing, and deploying applications and ML models; containerise applications (Docker) and assist in orchestration (Kubernetes or cloud services) to ensure smooth deployment of scalable solutions. Work closely with data scientists to deploy machine learning models into production environments; optimise model inference performance (leveraging frameworks like TensorFlow or PyTorch for model serving) and implement monitoring to track model performance, accuracy, and reliability post deployment. Keep up to date with the latest developments in Python, AI/ML technologies, and software engineering best practices; proactively suggest improvements to systems and processes, and contribute to architectural decisions that enhance the capabilities or performance of our AI solutions. Provide technical guidance and mentorship to Junior Engineers. Qualifications Bachelor's degree in Computer Science, Engineering, or related field (or equivalent work experience); a Master's degree or specialization in Artificial Intelligence/Machine Learning is a plus. Must have 8 years' experience working as a Software Engineer on large software applications. Proficient in technologies including Python, REST, PyTorch, TensorFlow, Docker, FastAPI, Selenium, React, TypeScript, Redux, GraphQL, Kafka, and Apache Spark. Experience working with one or more of the following database systems: DynamoDB, DocumentDB, MongoDB. Demonstrated expertise in unit testing and tools such as JUnit, Mockito, PyTest, and Selenium. Strong working knowledge of the PyData stack-pandas, NumPy for data manipulation; Jupyter Notebooks for experimentation; matplotlib/Seaborn for basic visualisation, and experience with data analysis and troubleshooting data related issues. Knowledge of design patterns and software architectures. Familiarity with CI/CD and automation tools; experience using Git for version control and platforms like Bitbucket for code collaboration; knowledge of build tools and pipeline configuration (Jenkins) to automate testing and deployment. Strong problem solving and analytical skills. Presentation and teamwork skills. Understanding of both Waterfall and Agile methodologies.
Senior Software Engineer - Pricing AI (Manchester) The Role We are seeking a talented Senior Developer with a strong focus on Python-based AI/ML development, automation, and general software engineering. The successful candidate will play a key role in building and deploying machine learning features and data-driven applications. You will work on end-to-end solutions - from writing robust code and unit tests to developing APIs and integrating machine learning models into our product ecosystem. This role requires a mix of software engineering excellence, an eye for automation, and hands on experience with AI/ML frameworks. If you are passionate about leveraging Python to solve complex problems and deliver scalable AI solutions, we want to hear from you. Experience in the travel or retail industry would be an advantage. Responsibilities Design, implement, and maintain software components that incorporate machine learning algorithms and data processing, and develop clean, efficient Python code for both backend logic and integration of ML models. Understand the business drivers behind each feature. Create and optimise data pipelines to collect, preprocess, and transform data for machine learning and analytics; work with large datasets, ensuring data quality and availability for training and prediction tasks. Develop robust RESTful APIs and microservices (using frameworks like FastAPI or Flask) to expose machine learning functionalities and data services; ensure APIs are secure, well documented, and perform at scale. Write and maintain comprehensive tests for your code; use PyTest for unit testing and Selenium (where appropriate) for end to end or UI testing to automate quality assurance; ensure that new features have proper test coverage and meet quality standards before deployment. Collaborate with DevOps engineers to set up and maintain CI/CD pipelines for building, testing, and deploying applications and ML models; containerise applications (Docker) and assist in orchestration (Kubernetes or cloud services) to ensure smooth deployment of scalable solutions. Work closely with data scientists to deploy machine learning models into production environments; optimise model inference performance (leveraging frameworks like TensorFlow or PyTorch for model serving) and implement monitoring to track model performance, accuracy, and reliability post deployment. Keep up to date with the latest developments in Python, AI/ML technologies, and software engineering best practices; proactively suggest improvements to systems and processes, and contribute to architectural decisions that enhance the capabilities or performance of our AI solutions. Provide technical guidance and mentorship to Junior Engineers. Qualifications Bachelor's degree in Computer Science, Engineering, or related field (or equivalent work experience); a Master's degree or specialization in Artificial Intelligence/Machine Learning is a plus. Must have 8 years' experience working as a Software Engineer on large software applications. Proficient in technologies including Python, REST, PyTorch, TensorFlow, Docker, FastAPI, Selenium, React, TypeScript, Redux, GraphQL, Kafka, and Apache Spark. Experience working with one or more of the following database systems: DynamoDB, DocumentDB, MongoDB. Demonstrated expertise in unit testing and tools such as JUnit, Mockito, PyTest, and Selenium. Strong working knowledge of the PyData stack-pandas, NumPy for data manipulation; Jupyter Notebooks for experimentation; matplotlib/Seaborn for basic visualisation, and experience with data analysis and troubleshooting data related issues. Knowledge of design patterns and software architectures. Familiarity with CI/CD and automation tools; experience using Git for version control and platforms like Bitbucket for code collaboration; knowledge of build tools and pipeline configuration (Jenkins) to automate testing and deployment. Strong problem solving and analytical skills. Presentation and teamwork skills. Understanding of both Waterfall and Agile methodologies.
Vermelo RPO
Job title: Senior Data Scientist Locations: Manchester or Haywards Heath (hybrid working) Markerstudy Group are looking for a Senior Data Scientist to join a quickly growing company in developing ambitious solutions across a range of insurance lines, by leveraging vast data assets and state-of-the-art processing capabilities. Markerstudy is a leading provider of private insurance in the UK, insuring around 5% of the private cars on the UK roads, 20% of commercial vehicles and over 30% of motorcycles in total premium levels of circa £1b. The majority of business is written as the insurance pricing provider behind household names such as Tesco, Sainsbury's, O2, Halifax, AA, Saga and Lloyds Bank to list a few. Role overview As a Senior Data Scientist, you will use your advanced analytical skills to: Lead the development of cutting-edge, bespoke machine learning predictive models, including risk pricing and classification and regression models Identify and create data solutions that create value Work collaboratively with the pricing and machine learning teams to provide insight across the business Your ideas and solutions will enable improvements to products, prices and processes giving Markerstudy a critical advantage in the increasingly competitive insurance market Identify and create solutions that leverage vast data assets and lead the development of bespoke machine-learning models to improve the underwriting performance of the Group. Key Responsibilities: Develop and test modelling improvements for pricing models, particularly in motor. These might include improvements in hyper-parameter tuning methods, model performance, model stability and feature explainability Be the technical lead in the development of predictive models that solve business challenges through one-off analyses or bespoke modelling. Such work would include risk classification, such as area or vehicle classification, as well as predictive models for other business use cases such as conversion, retention or price optimisation Prototype ML solutions before handing to the ML team for implementation Conduct more advanced yet focused research and development to solve business challenges Work collaboratively with other teams to analyse and identify improvements to risk modelling and wider business challenges Use a wide range of data science and statistical techniques Research and leverage new and existing internal and/or external data sources Communicate results to key decision makers across the business Assist in the deployment and monitoring effort to ensure efficient implementation of the solutions created Key Skills and Experience: PhD. or masters in statistics, data science or equivalent field or Degree with number of years of relevant experience Previous experience within data science Experience in insurance pricing and modelling Experience and detailed technical knowledge of GLMs /Elastic Nets, GBMs, GAMs, Random Forests, Neural Networks and clustering techniques Knowledge of statistics and distributions commonly used in insurance Experience in programming languages (e.g. Python, PySpark, R, SAS, SQL) Proficient at communicating results in a concise manner both verbally and written Behaviours: Motivated by technical excellence Driven to deliver iterative improvements in a timely fashion Team player Self-motivated with a drive to learn and develop Logical thinker with a professional and positive attitude
Job title: Senior Data Scientist Locations: Manchester or Haywards Heath (hybrid working) Markerstudy Group are looking for a Senior Data Scientist to join a quickly growing company in developing ambitious solutions across a range of insurance lines, by leveraging vast data assets and state-of-the-art processing capabilities. Markerstudy is a leading provider of private insurance in the UK, insuring around 5% of the private cars on the UK roads, 20% of commercial vehicles and over 30% of motorcycles in total premium levels of circa £1b. The majority of business is written as the insurance pricing provider behind household names such as Tesco, Sainsbury's, O2, Halifax, AA, Saga and Lloyds Bank to list a few. Role overview As a Senior Data Scientist, you will use your advanced analytical skills to: Lead the development of cutting-edge, bespoke machine learning predictive models, including risk pricing and classification and regression models Identify and create data solutions that create value Work collaboratively with the pricing and machine learning teams to provide insight across the business Your ideas and solutions will enable improvements to products, prices and processes giving Markerstudy a critical advantage in the increasingly competitive insurance market Identify and create solutions that leverage vast data assets and lead the development of bespoke machine-learning models to improve the underwriting performance of the Group. Key Responsibilities: Develop and test modelling improvements for pricing models, particularly in motor. These might include improvements in hyper-parameter tuning methods, model performance, model stability and feature explainability Be the technical lead in the development of predictive models that solve business challenges through one-off analyses or bespoke modelling. Such work would include risk classification, such as area or vehicle classification, as well as predictive models for other business use cases such as conversion, retention or price optimisation Prototype ML solutions before handing to the ML team for implementation Conduct more advanced yet focused research and development to solve business challenges Work collaboratively with other teams to analyse and identify improvements to risk modelling and wider business challenges Use a wide range of data science and statistical techniques Research and leverage new and existing internal and/or external data sources Communicate results to key decision makers across the business Assist in the deployment and monitoring effort to ensure efficient implementation of the solutions created Key Skills and Experience: PhD. or masters in statistics, data science or equivalent field or Degree with number of years of relevant experience Previous experience within data science Experience in insurance pricing and modelling Experience and detailed technical knowledge of GLMs /Elastic Nets, GBMs, GAMs, Random Forests, Neural Networks and clustering techniques Knowledge of statistics and distributions commonly used in insurance Experience in programming languages (e.g. Python, PySpark, R, SAS, SQL) Proficient at communicating results in a concise manner both verbally and written Behaviours: Motivated by technical excellence Driven to deliver iterative improvements in a timely fashion Team player Self-motivated with a drive to learn and develop Logical thinker with a professional and positive attitude
Ernst & Young Advisory Services Sdn Bhd
Manchester, Lancashire
At EY, we're all in to shape your future with confidence. We'll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world. Location : Manchester Position Overview We are seeking a highly skilled AI Engineer with proven expertise in developing and deploying advanced machine learning and large language model (LLM) solutions that drive measurable business impact. This role requires hands on experience building AI models and automation pathways across diverse use cases including finance forecasting, energy optimization, predictive maintenance, supply chain planning, and commercial transformation, leveraging modern cloud based AI platforms. Develop, and deploy end-to-end machine learning models for complex business problems across forecasting, optimization, and prediction domains Build and fine-tune large language models (LLMs) for enterprise applications including document intelligence, conversational AI, and decision support systems Deep understanding of solving data science and AI enabled problems in supply chain, finance, commercial or operations domain or AI agents with reasoning capabilities using LLMs Adapt to a wide range of technical challenges across technologies to design a solution applicable to the business issue Translate business requirements into technical AI/ML features, model selection, architecture decisions Conduct exploratory data analysis and communicate insights Collaborate with data engineers, architects, and business analysts on integrated solutions Build feature engineering pipelines and automated data preparation workflows Design AI solutions for commercial transformation including pricing optimization, customer segmentation, and revenue management Develop scalable AI/ML pipelines on Databricks, Azure Machine Learning, and/or Snowflake platforms Contribute to proposals and technical assessments for new opportunities and internal knowledge transfer Essential Qualifications Degree or equivalent certification in Computer Science, Data Science, Statistics, Mathematics, Engineering, or related quantitative field Proven experience building and implementing LLM-based solutions (GPT, Claude, Llama, Mistral, or similar) Hands on experience with at least one of: Databricks (MLflow, AutoML), Azure Machine Learning, or Snowflake (Snowpark ML, Cortex) Understanding of natural language processing, computer vision, and recommender systems Strong programming skills in Python, SQL and proficiency with ML libraries (scikit learn, pandas, NumPy, XGBoost, LightGBM) Strong analytical and problem solving mindset with attention to detail Ability to work independently and drive projects from ambiguous requirements Story telling with data and insights from the outputs Consulting skills, supporting development of presentation decks and communication Preferred Criteria Experience or knowledge covering at least one of the following areas: Deep understanding of machine learning algorithms including supervised, unsupervised, and reinforcement learning approaches Strong proficiency in statistical modelling, time series forecasting, and predictive analytics Experience with deep learning frameworks (TensorFlow, PyTorch, Keras) Knowledge of prompt engineering, RAG (Retrieval Augmented Generation), and LLM fine tuning techniques Familiarity with distributed computing frameworks (eg Spark) Knowledge of graph neural networks, reinforcement learning, or causal inference Experience with AI governance, model risk management, and regulatory compliance Experience using Pro code and Low code tools such as LangGraph, AutoGen, Semantic Kernal and MS CoPilot Experience in any of the following: Finance Forecasting: Revenue prediction, cashflow modelling, financial planning, risk modelling Energy Optimization: Load forecasting, grid optimization, demand response, renewable energy prediction Predictive Maintenance: Equipment failure prediction, anomaly detection, remaining useful life estimation Supply Chain Planning: Demand forecasting, inventory optimisation, logistics planning, procurement analytics Commercial Transformation: Price optimisation, customer lifetime value, churn prediction, marketing mix modelling Preferred Qualifications Certifications such as: Databricks Certified Machine Learning Professional Azure AI Engineer Associate or Data Scientist Associate SnowPro Advanced: Data Scientist AWS Certified Machine Learning - Specialty EY Building a better working world EY is building a better working world by creating new value for clients, people, society and the planet, while building trust in capital markets. Enabled by data, AI and advanced technology, EY teams help clients shape the future with confidence and develop answers for the most pressing issues of today and tomorrow. EY teams work across a full spectrum of services in assurance, consulting, tax, strategy and transactions. Fueled by sector insights, a globally connected, multi disciplinary network and diverse ecosystem partners, EY teams can provide services in more than 150 countries and territories.
At EY, we're all in to shape your future with confidence. We'll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world. Location : Manchester Position Overview We are seeking a highly skilled AI Engineer with proven expertise in developing and deploying advanced machine learning and large language model (LLM) solutions that drive measurable business impact. This role requires hands on experience building AI models and automation pathways across diverse use cases including finance forecasting, energy optimization, predictive maintenance, supply chain planning, and commercial transformation, leveraging modern cloud based AI platforms. Develop, and deploy end-to-end machine learning models for complex business problems across forecasting, optimization, and prediction domains Build and fine-tune large language models (LLMs) for enterprise applications including document intelligence, conversational AI, and decision support systems Deep understanding of solving data science and AI enabled problems in supply chain, finance, commercial or operations domain or AI agents with reasoning capabilities using LLMs Adapt to a wide range of technical challenges across technologies to design a solution applicable to the business issue Translate business requirements into technical AI/ML features, model selection, architecture decisions Conduct exploratory data analysis and communicate insights Collaborate with data engineers, architects, and business analysts on integrated solutions Build feature engineering pipelines and automated data preparation workflows Design AI solutions for commercial transformation including pricing optimization, customer segmentation, and revenue management Develop scalable AI/ML pipelines on Databricks, Azure Machine Learning, and/or Snowflake platforms Contribute to proposals and technical assessments for new opportunities and internal knowledge transfer Essential Qualifications Degree or equivalent certification in Computer Science, Data Science, Statistics, Mathematics, Engineering, or related quantitative field Proven experience building and implementing LLM-based solutions (GPT, Claude, Llama, Mistral, or similar) Hands on experience with at least one of: Databricks (MLflow, AutoML), Azure Machine Learning, or Snowflake (Snowpark ML, Cortex) Understanding of natural language processing, computer vision, and recommender systems Strong programming skills in Python, SQL and proficiency with ML libraries (scikit learn, pandas, NumPy, XGBoost, LightGBM) Strong analytical and problem solving mindset with attention to detail Ability to work independently and drive projects from ambiguous requirements Story telling with data and insights from the outputs Consulting skills, supporting development of presentation decks and communication Preferred Criteria Experience or knowledge covering at least one of the following areas: Deep understanding of machine learning algorithms including supervised, unsupervised, and reinforcement learning approaches Strong proficiency in statistical modelling, time series forecasting, and predictive analytics Experience with deep learning frameworks (TensorFlow, PyTorch, Keras) Knowledge of prompt engineering, RAG (Retrieval Augmented Generation), and LLM fine tuning techniques Familiarity with distributed computing frameworks (eg Spark) Knowledge of graph neural networks, reinforcement learning, or causal inference Experience with AI governance, model risk management, and regulatory compliance Experience using Pro code and Low code tools such as LangGraph, AutoGen, Semantic Kernal and MS CoPilot Experience in any of the following: Finance Forecasting: Revenue prediction, cashflow modelling, financial planning, risk modelling Energy Optimization: Load forecasting, grid optimization, demand response, renewable energy prediction Predictive Maintenance: Equipment failure prediction, anomaly detection, remaining useful life estimation Supply Chain Planning: Demand forecasting, inventory optimisation, logistics planning, procurement analytics Commercial Transformation: Price optimisation, customer lifetime value, churn prediction, marketing mix modelling Preferred Qualifications Certifications such as: Databricks Certified Machine Learning Professional Azure AI Engineer Associate or Data Scientist Associate SnowPro Advanced: Data Scientist AWS Certified Machine Learning - Specialty EY Building a better working world EY is building a better working world by creating new value for clients, people, society and the planet, while building trust in capital markets. Enabled by data, AI and advanced technology, EY teams help clients shape the future with confidence and develop answers for the most pressing issues of today and tomorrow. EY teams work across a full spectrum of services in assurance, consulting, tax, strategy and transactions. Fueled by sector insights, a globally connected, multi disciplinary network and diverse ecosystem partners, EY teams can provide services in more than 150 countries and territories.
