Synthesia Limited
Synthesia is the world's leading AI video platform for business, used by over 90% of the Fortune 100. Founded in 2017, the company is headquartered in London, with offices and teams across Europe and the US. As AI continues to shape the way we live and work, Synthesia develops products to enhance visual communication and enterprise skill development, helping people work better and stay at the center of successful organizations. Following our recent Series E funding round, where we raised $200 million, our valuation stands at $4 billion. Our total funding exceeds $530 million from premier investors including Accel, NVentures (Nvidia's VC arm), Kleiner Perkins, GV, and Evantic Capital, alongside the founders and operators of Stripe, Datadog, Miro, and Webflow. Role Purpose We're looking for a Senior Data Scientist (L5) to join our Product Data team collaborating with our Product Analysts to build deep understanding of how users engage with our AI-native products through conversation and interaction data. You will work at scale with unstructured text data - prompts, model outputs, user edits, feedback - to discover patterns that explain user behaviour and directly shape what we build next. The focus is on semantic analysis of conversations: understanding intent, identifying failure modes, detecting successful interaction patterns, and translating these insights into specific product improvements. This is hands on analytical work, not infrastructure-focused. We need someone who can analyse messy conversation data, discover non-obvious patterns, and connect those findings to product decisions that move the needle on adoption, retention, and cost efficiency. For exceptional candidates with track records of leading analytics in AI-driven environments, we are open to hiring at Principal level, where you would set the broader data science agenda and mentor the existing analytics team. What You'll Do Build product evaluation frameworks Define how we measure "good" for AI-native features beyond traditional funnels. Build semantic frameworks to categorise user intent, model behaviour, and interaction patterns - e.g., "What types of prompts succeed vs. fail? What causes users to retry? What signals indicate satisfaction?" Design feedback loops that connect prompts, model outputs, user behaviour, and downstream outcomes. Define, track, and own the metrics that leadership and product teams depend on for a shared, trustworthy view of what is working and what is not. Analyse user-AI interactions at scale Work with large conversation datasets to deeply analyse how users interact with AI features (prompts, edits, retries, acceptance, abandonment). Identify failure patterns, unnecessary iteration loops, and the characteristics of successful interactions. Build models that answer the questions dashboards cannot: what predicts a good user outcome, what drives failure, and where the highest-leverage improvements are. Shape the product roadmap Turn findings into specific, prioritised recommendations that feed directly into the product roadmap. Partner with Product and Engineering to evaluate iterations quickly and close the loop between insight and action. Run experiments end-to-end: design, instrument, analyse, and translate results into clear product decisions. Drive growth and financial metrics Link AI feature usage to activation, retention, expansion, and cost efficiency. Help answer questions like: Which interactions create durable value? Where are we over spending compute for low user impact? Build infrastructure and raise the bar Build pipelines, dashboards, and self-serve analytical tools that make insight accessible and trustworthy across the organisation. Mentor a team of product analysts, raising the technical bar and introducing new methods where they add real value. What We're Looking For Experience Significant experience (ideally 5+ years) in Data Science, Product Analytics, or a similar role with conversation, chat, or dialogue data at scale. You have actually analysed large volumes of user text (prompts, messages, feedback, reviews) to discover patterns that shaped product decisions. Experience working closely with Product and Engineering teams. Hands on experience working with AI/ML-driven products (LLMs, ranking, generation, recommendations). You have worked on these systems, not just alongside them. Skillset Strong applied modelling skills: regression, classification, clustering, survival analysis, or similar. You pick the method that fits the question, not the other way around. Deep expertise in experimentation design and statistical inference. You can design a valid experiment, choose the right test, and explain the results to a non-technical audience. Fluency in SQL and Python. Comfortable working with large, messy, high-dimensional interaction data and building reproducible analysis pipelines. Ability to design pragmatic evaluation metrics where ground truth is fuzzy. Familiarity with modern data stack tools: dbt, Snowflake, Hex, Omni, Looker, or similar. Clear communicator who can influence without authority. Nice to Have Experience with product analytics platforms (e.g. Amplitude, Mixpanel, or similar). Experience working with NLP, text analytics, or unstructured data at scale. Experience building semantic search, relevance scoring, or interaction-based evaluation systems. Familiarity with prompt analytics, embedding-based analysis, or clustering user behaviour. Track record of influencing product strategy at a senior level, not just delivering analyses. Experience mentoring or technically leading other analysts or data scientists. Our culture At Synthesia we're passionate about building, not talking, planning or politicising. We strive to hire the smartest, kindest and most unrelenting people and let them do their best work without distractions. Our work principles serve as our charter for how we make decisions, give feedback and structure our work to empower everyone to go as fast as possible. You can find out more about these principles here. Benefits You will be compensated well with a generous salary and equity Flexible, remote-friendly role for team members working in UK/Europe You get 25 days of annual leave + local holidays Regular team offsites where you'll get to collaborate with the product & engineering team in person Work from home budget "Work from anywhere" up to 60 days per year Generous referral scheme of up to $10,000 USD for each successful referral
Synthesia is the world's leading AI video platform for business, used by over 90% of the Fortune 100. Founded in 2017, the company is headquartered in London, with offices and teams across Europe and the US. As AI continues to shape the way we live and work, Synthesia develops products to enhance visual communication and enterprise skill development, helping people work better and stay at the center of successful organizations. Following our recent Series E funding round, where we raised $200 million, our valuation stands at $4 billion. Our total funding exceeds $530 million from premier investors including Accel, NVentures (Nvidia's VC arm), Kleiner Perkins, GV, and Evantic Capital, alongside the founders and operators of Stripe, Datadog, Miro, and Webflow. Role Purpose We're looking for a Senior Data Scientist (L5) to join our Product Data team collaborating with our Product Analysts to build deep understanding of how users engage with our AI-native products through conversation and interaction data. You will work at scale with unstructured text data - prompts, model outputs, user edits, feedback - to discover patterns that explain user behaviour and directly shape what we build next. The focus is on semantic analysis of conversations: understanding intent, identifying failure modes, detecting successful interaction patterns, and translating these insights into specific product improvements. This is hands on analytical work, not infrastructure-focused. We need someone who can analyse messy conversation data, discover non-obvious patterns, and connect those findings to product decisions that move the needle on adoption, retention, and cost efficiency. For exceptional candidates with track records of leading analytics in AI-driven environments, we are open to hiring at Principal level, where you would set the broader data science agenda and mentor the existing analytics team. What You'll Do Build product evaluation frameworks Define how we measure "good" for AI-native features beyond traditional funnels. Build semantic frameworks to categorise user intent, model behaviour, and interaction patterns - e.g., "What types of prompts succeed vs. fail? What causes users to retry? What signals indicate satisfaction?" Design feedback loops that connect prompts, model outputs, user behaviour, and downstream outcomes. Define, track, and own the metrics that leadership and product teams depend on for a shared, trustworthy view of what is working and what is not. Analyse user-AI interactions at scale Work with large conversation datasets to deeply analyse how users interact with AI features (prompts, edits, retries, acceptance, abandonment). Identify failure patterns, unnecessary iteration loops, and the characteristics of successful interactions. Build models that answer the questions dashboards cannot: what predicts a good user outcome, what drives failure, and where the highest-leverage improvements are. Shape the product roadmap Turn findings into specific, prioritised recommendations that feed directly into the product roadmap. Partner with Product and Engineering to evaluate iterations quickly and close the loop between insight and action. Run experiments end-to-end: design, instrument, analyse, and translate results into clear product decisions. Drive growth and financial metrics Link AI feature usage to activation, retention, expansion, and cost efficiency. Help answer questions like: Which interactions create durable value? Where are we over spending compute for low user impact? Build infrastructure and raise the bar Build pipelines, dashboards, and self-serve analytical tools that make insight accessible and trustworthy across the organisation. Mentor a team of product analysts, raising the technical bar and introducing new methods where they add real value. What We're Looking For Experience Significant experience (ideally 5+ years) in Data Science, Product Analytics, or a similar role with conversation, chat, or dialogue data at scale. You have actually analysed large volumes of user text (prompts, messages, feedback, reviews) to discover patterns that shaped product decisions. Experience working closely with Product and Engineering teams. Hands on experience working with AI/ML-driven products (LLMs, ranking, generation, recommendations). You have worked on these systems, not just alongside them. Skillset Strong applied modelling skills: regression, classification, clustering, survival analysis, or similar. You pick the method that fits the question, not the other way around. Deep expertise in experimentation design and statistical inference. You can design a valid experiment, choose the right test, and explain the results to a non-technical audience. Fluency in SQL and Python. Comfortable working with large, messy, high-dimensional interaction data and building reproducible analysis pipelines. Ability to design pragmatic evaluation metrics where ground truth is fuzzy. Familiarity with modern data stack tools: dbt, Snowflake, Hex, Omni, Looker, or similar. Clear communicator who can influence without authority. Nice to Have Experience with product analytics platforms (e.g. Amplitude, Mixpanel, or similar). Experience working with NLP, text analytics, or unstructured data at scale. Experience building semantic search, relevance scoring, or interaction-based evaluation systems. Familiarity with prompt analytics, embedding-based analysis, or clustering user behaviour. Track record of influencing product strategy at a senior level, not just delivering analyses. Experience mentoring or technically leading other analysts or data scientists. Our culture At Synthesia we're passionate about building, not talking, planning or politicising. We strive to hire the smartest, kindest and most unrelenting people and let them do their best work without distractions. Our work principles serve as our charter for how we make decisions, give feedback and structure our work to empower everyone to go as fast as possible. You can find out more about these principles here. Benefits You will be compensated well with a generous salary and equity Flexible, remote-friendly role for team members working in UK/Europe You get 25 days of annual leave + local holidays Regular team offsites where you'll get to collaborate with the product & engineering team in person Work from home budget "Work from anywhere" up to 60 days per year Generous referral scheme of up to $10,000 USD for each successful referral
Synthesia Limited
Synthesia is the world's leading AI video platform for business, used by over 90% of the Fortune 100. Founded in 2017, the company is headquartered in London, with offices and teams across Europe and the US. As AI continues to shape the way we live and work, Synthesia develops products to enhance visual communication and enterprise skill development, helping people work better and stay at the center of successful organizations. Following our recent Series E funding round, where we raised $200 million, our valuation stands at $4 billion. Our total funding exceeds $530 million from premier investors including Accel, NVentures (Nvidia's VC arm), Kleiner Perkins, GV, and Evantic Capital, alongside the founders and operators of Stripe, Datadog, Miro, and Webflow. About the role As a Technical Support Associate at Synthesia, you'll be part of the team ensuring delivering first-line technical support to enterprise customers. You'll assist with technical investigations, resolve customer issues, and learn to handle more complex cases as you develop your technical and analytical skills. You'll work closely with experienced Technical Support Specialists and Engineers, gaining exposure to a wide range of technical systems while supporting customers and internal teams. This is a great opportunity to start or advance your career in technical support within a fast-paced, innovative SaaS company. Role Responsibilities Provide first-line technical support to enterprise customers mainly via live chat, investigating and resolving platform issues Gather and document all relevant information for reported issues, ensuring accurate case creation and updates Apply standard troubleshooting techniques and validated fixes under guidance from senior team members Escalate more complex or critical issues to Technical Support Specialists or Engineering with clear diagnostic details Reproduce reported issues in internal environments to support investigations Follow up with customers to ensure issues are resolved to satisfaction Maintain clear, professional communication with customers throughout the support process Document solutions, troubleshooting steps, and new learnings for internal knowledge sharing About You 1 to 3 years' experience in a technical support, helpdesk, or customer-facing technical role (or equivalent practical experience) Strong interest in software, systems troubleshooting, and delivering excellent customer outcomes Confident and clear communicator, with the ability to explain technical concepts to non-technical users Highly organised with strong analytical and problem-solving skills, and attention to detail Comfortable taking ownership of issues and managing multiple cases in parallel Curious, proactive learner who enjoys developing technical depth and understanding new tools Collaborative team player who contributes positively to team discussions and continuous improvement Technical Experience (Preferred but not Required) Basic understanding of SaaS platforms and web technologies Familiarity with basic browser troubleshooting and developer tools Experience using ticketing systems such as Intercom, Jira, or Salesforce Awareness of SSO concepts and authentication flows Interest in APIs, data analysis, or system integrations Exposure to log analysis or monitoring platforms (e.g. Datadog) Success will be measured on Key Performance Indicators (KPI's) within the support team, including but not limited to: Customer Satisfaction (CSAT) First Response Time SLA Compliance Productivity metrics
Synthesia is the world's leading AI video platform for business, used by over 90% of the Fortune 100. Founded in 2017, the company is headquartered in London, with offices and teams across Europe and the US. As AI continues to shape the way we live and work, Synthesia develops products to enhance visual communication and enterprise skill development, helping people work better and stay at the center of successful organizations. Following our recent Series E funding round, where we raised $200 million, our valuation stands at $4 billion. Our total funding exceeds $530 million from premier investors including Accel, NVentures (Nvidia's VC arm), Kleiner Perkins, GV, and Evantic Capital, alongside the founders and operators of Stripe, Datadog, Miro, and Webflow. About the role As a Technical Support Associate at Synthesia, you'll be part of the team ensuring delivering first-line technical support to enterprise customers. You'll assist with technical investigations, resolve customer issues, and learn to handle more complex cases as you develop your technical and analytical skills. You'll work closely with experienced Technical Support Specialists and Engineers, gaining exposure to a wide range of technical systems while supporting customers and internal teams. This is a great opportunity to start or advance your career in technical support within a fast-paced, innovative SaaS company. Role Responsibilities Provide first-line technical support to enterprise customers mainly via live chat, investigating and resolving platform issues Gather and document all relevant information for reported issues, ensuring accurate case creation and updates Apply standard troubleshooting techniques and validated fixes under guidance from senior team members Escalate more complex or critical issues to Technical Support Specialists or Engineering with clear diagnostic details Reproduce reported issues in internal environments to support investigations Follow up with customers to ensure issues are resolved to satisfaction Maintain clear, professional communication with customers throughout the support process Document solutions, troubleshooting steps, and new learnings for internal knowledge sharing About You 1 to 3 years' experience in a technical support, helpdesk, or customer-facing technical role (or equivalent practical experience) Strong interest in software, systems troubleshooting, and delivering excellent customer outcomes Confident and clear communicator, with the ability to explain technical concepts to non-technical users Highly organised with strong analytical and problem-solving skills, and attention to detail Comfortable taking ownership of issues and managing multiple cases in parallel Curious, proactive learner who enjoys developing technical depth and understanding new tools Collaborative team player who contributes positively to team discussions and continuous improvement Technical Experience (Preferred but not Required) Basic understanding of SaaS platforms and web technologies Familiarity with basic browser troubleshooting and developer tools Experience using ticketing systems such as Intercom, Jira, or Salesforce Awareness of SSO concepts and authentication flows Interest in APIs, data analysis, or system integrations Exposure to log analysis or monitoring platforms (e.g. Datadog) Success will be measured on Key Performance Indicators (KPI's) within the support team, including but not limited to: Customer Satisfaction (CSAT) First Response Time SLA Compliance Productivity metrics
Synthesia Limited
What You'll Do: Review deal submissions from EMEA AE/CSMs for compliance with pricing policy, discount schedules, and approval thresholds-approving standard deals and routing exceptions to senior reviewers Support modelling of multi-year, multi-product deals-building ARR, TCV, and per-seat/platform fee scenarios under the guidance of senior team members Spot common commercial risks in deal structures and flag them to senior team members or the Manager for review Triage exception requests, gather supporting context from the AE/CSM, and prepare them for review by senior team members with clear documentation Commercial Operations & Systems Manage deal data integrity in Salesforce-ensuring opportunity records, pricing fields, and approval audit trails are accurate and complete Work within DealHub (CPQ) to validate deal configurations, flag misconfigurations, and escalare system issues during the deal review workflow Support ARR and revenue recognition hygiene by flagging deal structures that may create recognition complexity for senior review Assist with maintaining Deal Desk playbooks, floor pricing references, and discount schedule documentation Stakeholder Partnership Act as a first point of contact for EMEA AE/CSMs on standard commercial queries and deal submission questions, escalating senior or complex requests as needed Coordinate with Finance and Legal on routine deal questions, escalating non-standard commercial terms or booking issues to senior team members Communicate approval decisions clearly-explaining the why, not just the outcome, and building AE/CSM trust through consistency and speed Manage inbound deal desk cases from the EMEA field-triaging requests from AE/CSMs via the shared deal desk mailbox, tracking case status, and ensuring SLAs are met for standard submissions Process Ownership Maintain deal log accuracy, hit SLAs consistently, and surface observations on recurring approval patterns to the Manager Flag recurring exceptions to the Director that may signal a gap in the approval framework Help roll out new commercial policies into the EMEA field by maintaining documentation and supporting enablement sessions Experience & Technical Skills At least 2 years of experience in a Deal Desk, Sales Operations, Revenue Operations, or commercial finance role in a B2B SaaS company Hands on Salesforce experience-navigate opportunity records, run reports, and maintain deal data accuracy independently Familiarity with CPQ systems (DealHub, Salesforce CPQ, or similar)-understand how deal configurations map to pricing outputs Working knowledge of revenue recognition principles (ASC 606 / IFRS 15)-identify when a deal structure creates a recognition issue and escalatate appropriately Comfort building and interpreting deal models in Excel or Google Sheets-ARR/TCV splits, multi year commit scenarios, discount waterfall logic What You'll Bring Working understanding of SaaS commercial mechanics: ARR, TCV, per-seat pricing, platform fees, multi-year discounting Clear, confident communicator-comfortable fielding questions from AE/CSMs and asking for help when a deal is outside your remit Highly organized with a low error rate on repetitive, process-driven tasks Proactive by default-flag problems early rather than waiting to be asked EMEA-based and comfortable spanning UK, DACH, Nordics, and broader European deal cycles Nice to Have Experience with CLM platforms (Ironclad, LinkSquares, Luminance, or similar) Exposure to AWS Marketplace or other cloud marketplace deal mechanics Experience supporting a Deal Desk or RevOps tooling implementation Familiarity with NetSuite for order management or billing workflows Knowledge of EMEA-specific commercial nuances: GDPR data processing terms, EU procurement cycles, local PO and invoicing requirements In addition to being a part of a great team, working in a fun and innovative environment, we offer the following benefits: A competitive salary + stock options in our fast-growing Series E start-up Paid parental leave entitling primary caregivers to 16 weeks of full pay, and secondary 5 weeks of full pay 25 days of annual leave + public holidays in the country where you are based Cycle to work scheme (London) Regular socials Private Medical Insurance (Medical History Disregarded basis) including mental health support, dental & vision, cashback and gym discounts (UK) A generous referral scheme Pension contribution / salary sacrifice Work from home set up A huge opportunity for career growth as you'll help shape a market-defining product UK Benefits (for region-specific, see here)
What You'll Do: Review deal submissions from EMEA AE/CSMs for compliance with pricing policy, discount schedules, and approval thresholds-approving standard deals and routing exceptions to senior reviewers Support modelling of multi-year, multi-product deals-building ARR, TCV, and per-seat/platform fee scenarios under the guidance of senior team members Spot common commercial risks in deal structures and flag them to senior team members or the Manager for review Triage exception requests, gather supporting context from the AE/CSM, and prepare them for review by senior team members with clear documentation Commercial Operations & Systems Manage deal data integrity in Salesforce-ensuring opportunity records, pricing fields, and approval audit trails are accurate and complete Work within DealHub (CPQ) to validate deal configurations, flag misconfigurations, and escalare system issues during the deal review workflow Support ARR and revenue recognition hygiene by flagging deal structures that may create recognition complexity for senior review Assist with maintaining Deal Desk playbooks, floor pricing references, and discount schedule documentation Stakeholder Partnership Act as a first point of contact for EMEA AE/CSMs on standard commercial queries and deal submission questions, escalating senior or complex requests as needed Coordinate with Finance and Legal on routine deal questions, escalating non-standard commercial terms or booking issues to senior team members Communicate approval decisions clearly-explaining the why, not just the outcome, and building AE/CSM trust through consistency and speed Manage inbound deal desk cases from the EMEA field-triaging requests from AE/CSMs via the shared deal desk mailbox, tracking case status, and ensuring SLAs are met for standard submissions Process Ownership Maintain deal log accuracy, hit SLAs consistently, and surface observations on recurring approval patterns to the Manager Flag recurring exceptions to the Director that may signal a gap in the approval framework Help roll out new commercial policies into the EMEA field by maintaining documentation and supporting enablement sessions Experience & Technical Skills At least 2 years of experience in a Deal Desk, Sales Operations, Revenue Operations, or commercial finance role in a B2B SaaS company Hands on Salesforce experience-navigate opportunity records, run reports, and maintain deal data accuracy independently Familiarity with CPQ systems (DealHub, Salesforce CPQ, or similar)-understand how deal configurations map to pricing outputs Working knowledge of revenue recognition principles (ASC 606 / IFRS 15)-identify when a deal structure creates a recognition issue and escalatate appropriately Comfort building and interpreting deal models in Excel or Google Sheets-ARR/TCV splits, multi year commit scenarios, discount waterfall logic What You'll Bring Working understanding of SaaS commercial mechanics: ARR, TCV, per-seat pricing, platform fees, multi-year discounting Clear, confident communicator-comfortable fielding questions from AE/CSMs and asking for help when a deal is outside your remit Highly organized with a low error rate on repetitive, process-driven tasks Proactive by default-flag problems early rather than waiting to be asked EMEA-based and comfortable spanning UK, DACH, Nordics, and broader European deal cycles Nice to Have Experience with CLM platforms (Ironclad, LinkSquares, Luminance, or similar) Exposure to AWS Marketplace or other cloud marketplace deal mechanics Experience supporting a Deal Desk or RevOps tooling implementation Familiarity with NetSuite for order management or billing workflows Knowledge of EMEA-specific commercial nuances: GDPR data processing terms, EU procurement cycles, local PO and invoicing requirements In addition to being a part of a great team, working in a fun and innovative environment, we offer the following benefits: A competitive salary + stock options in our fast-growing Series E start-up Paid parental leave entitling primary caregivers to 16 weeks of full pay, and secondary 5 weeks of full pay 25 days of annual leave + public holidays in the country where you are based Cycle to work scheme (London) Regular socials Private Medical Insurance (Medical History Disregarded basis) including mental health support, dental & vision, cashback and gym discounts (UK) A generous referral scheme Pension contribution / salary sacrifice Work from home set up A huge opportunity for career growth as you'll help shape a market-defining product UK Benefits (for region-specific, see here)