Data Scientist

• Lead DTS Development: Author and manage Data Transfer Specifications (DTS) to align external data providers and research partners on required data structures, formats, and templates.
• Oversee Data Standardization: Ensure study teams adhere to CDISC standards for external data, including biomarkers, wearable devices, IRT, imaging, and eCOA.
• Cross-Functional Collaboration: Serve as the primary contact for external data quality control, participating as an extended member of the Clinical Study Team and facilitating new test codes.
• Vendor & Process Management: Provide operational oversight to external data vendors, manage change requests for existing DTS, and contribute to continuous process improvement initiatives.
• Data Reconciliation & Compliance: Support data reconciliation, resolve structure inquiries, and comply with all regulatory requirements, including clinical protocols and analysis expectations.

Senior Lead Clinical Data Science Programmer

• **About the Role**
• Few teams use phone sensor data to price commercial motor insurance at scale. As a Senior Data Scientist, you'll shape how millions of trips are turned into risk signals. You'll own behavioural features and algorithms from hypothesis to production, working at the intersection of data science and engineering on GPS, inertial, and other sensor data.
• You'll move between quick heuristics and full ML models depending on what the problem calls for. You ship code to production, not just notebooks.

Senior Data Scientist – Telematics

• Partner with Product and BI to turn business goals into well-scoped ML problems with clear success criteria and guardrails.
• Build and productionize models for segmentation, churn, LTV, and recommendations.
• Design evaluation frameworks including offline benchmarks and online feedback loops to ensure models are measured, not assumed.
• Collaborate with Engineering on production design considerations like latency, payload structure, fallbacks, and failure modes.
• Monitor model performance over time, detect drift, and own retraining and iteration cycles.
• Use product telemetry and user feedback to drive continuous model and feature improvements.
• Work alongside AI coding agents to accelerate development (pipelines, tests, refactoring, exploration) while maintaining human oversight.
• Communicate results, trade-offs, and recommendations clearly across technical and non-technical teams.

• Design and build machine learning, NLP, and generative AI systems for scientific discovery, knowledge extraction, decision support, and intelligent content understanding.
• Work with large-scale, complex, and heterogeneous data, including scientific publications, research datasets, knowledge graphs, ontologies, taxonomies, citations, metadata, and content from every scientific discipline.
• Apply the right technique to each problem, using approaches such as classification, regression, clustering, ranking, feature engineering, deep learning, embeddings, LLMs, retrieval, and generative AI.
• Develop capabilities for semantic search, information retrieval, entity extraction, content classification, recommendation, ranking, summarization, question answering, and evidence-grounded generation.
• Build, evaluate, fine-tune, prompt, and integrate models into robust production systems, while continuously improving quality, relevance, reliability, and user value.
• Write clean, tested, production-quality Python and contribute reusable data science components, packages, and scalable data pipelines for preprocessing, inference, experimentation, monitoring, and continuous improvement.
• Support deployment, monitoring, model maintenance, drift detection, automated retraining, and ongoing optimization of data science systems.
• Collaborate with engineering, product, UX, analytics, research, and domain experts, and communicate technical concepts, model behavior, insights, trade-offs, and recommendations clearly to technical and non-technical audiences.

Data Scientist II

• Design and analyse A/B tests across Viator’s marketplace, applying sound statistical methods to interpret results and support confident decision-making
• Champion experimentation best practices: power calculations, guardrail metrics, and multiple testing corrections.
• Develop your mastery of causal inference and advanced experimentation techniques (e.g., difference-in-differences, propensity scoring, synthetic controls) as you apply them to answer questions that can't be randomized
• Own the measurement framework for your product area: define key metrics, build the instrumentation to track them, and surface insights that move the needle.
• Conduct exploratory analyses and deep dives into our data, using various data science approaches, to inform product decisions
• Enable self-service through scalable datasets, metrics, dashboards and reporting frameworks
• Translate analytical outputs into actionable insights and clear product recommendations
• Act as a thought partner with product managers and engineers to ensure the right data questions are being asked
• Translate analyses into clear narratives that are accessible to non-technical audiences

Product Data Scientist

• Own the execution of one or more production data science projects, translating broad problem statements into well-scoped tasks and credible analytical results that meet stakeholder expectations.
• Design, develop, and validate novel behavioral heuristics and algorithms over EVM (and other) blockchain data to attribute on-chain activity and uncover new insights.
• Apply advanced techniques including graph computation, statistical modeling, and machine learning to large-scale on-chain datasets.
• Identify and resolve inefficiencies in code, methodology, and workflows; ensure your work integrates cleanly into our production data and tooling stack.
• Clearly articulate and defend methodology and results to both technical and non-technical stakeholders, maintaining alignment through consistent communication.
• Mentor junior team members, contribute to technical hiring, and share knowledge.
• Collaborate closely with peers to bring research from prototype to production.

Senior Data Scientist

• Shape the Data & AI vision and go-to-market
• Drive revenue growth and pipeline development
• Build a scaled, high-performing capability
• Ensure high-quality, outcome-led delivery across key clients
• Work with the very latest Microsoft technologies, such as Microsoft Fabric, Power BI, Purview, and Microsoft Foundry
• Contribute to pre-sales activity by joining client calls, shaping proposals, and advising on solution approaches

Head of Data

• We’re hiring a senior data scientist to help stand up and scale a shared data science capability that partners with stream-aligned teams.
• You’ll report into the Data Science Team Manager and lead end‑to‑end DS/ML projects, shape standards, mentor teammates, and ship models into production, balancing quick wins with robust engineering.
• In particular, we are currently exploring ideas around using AI and OCR to process documents and learner work, and to validate marking consistency in a range of qualifications.
• Partner with stakeholders across the business to explore high‑impact opportunities.
• Own the full lifecycle: problem framing, data discovery, feature engineering, modelling, evaluation, deployment, monitoring, and iteration.
• Build and productionize LLM features where appropriate (retrieval‑augmented generation, evaluation, safety guardrails, cost/latency optimization) on AWS.
• Contribute to DS/ML standards: experimentation, model governance, documentation, and reproducibility.
• Mentor junior scientists, work with external contractors and collaborate closely with data engineering on pipelines and data quality.

• Develop a deep understanding of the data, its limitations and meaning, including the investigation of data validity
• Build and analyse data-driven predictive trading models
• Select or build model validation metrics to evaluate model performance
• Develop automated trading strategies - backtesting, paper and production trading

Trading Data Science Graduate

• Develop AI/ML and Generative AI / LLM models to address business problems
• Write patents and academic papers
• Define, create, and maintain actionable insights using data science
• Prepare analyses to support business decisions
• Collaborate with colleagues and subject matter experts
• Continuously grow and develop skills across AI/ML and GenAI
• Stay up to date with advances in AI/GenAI, and promote adoption of AI tools

• Play a pivotal role in evolving our data function from strong management information delivery to a data science-led, AI-enabled capability.
• Accountable for developing and deploying predictive and statistical models across complex datasets.
• Ensure solutions transition effectively from experimentation into robust, controlled and scalable production use.
• Lead a team of analysts, supporting performance, development plans, and day-to-day prioritisation.
• Partner with senior stakeholders across the UK Life Business to identify opportunities for deeper insight and improved decision-making.
• Lead the design and delivery of advanced analytics and data science-driven solutions, including predictive insight and trend analysis.
• Shape and oversee the responsible use of AI and GenAI to automate insight generation and repeatable MI processes.

Senior Data Science, Analytics Lead

• Support the development and maintenance of data driven agentic solutions
• Collaborate across teams to learn and apply established best practices and reusable components
• Execute analytical and modeling tasks as part of a larger project team
• Apply standard best practices to develop statistical and machine learning techniques to build models that address business needs
• Contribute to stakeholder communications by preparing summaries, documentation, and analysis
• Work with guidance to understand business problems and requirements and help identify appropriate modeling approaches
• Assist in developing prototypes and frameworks that integrate data and machine learning/predictive modeling into business decision making processes

Data Scientist – Agentic AI

• Primary Data Management (DM) contact (Lead DM role) for assigned clinical project(s) / program(s), ensuring that there is back-up, continuity, responsiveness, and that tasks are performed in a timely manner. May support another Lead DM as a back-up and/or team member. May include DM oversight of sponsor programs.
• Oversee project data entry process including development of data entry guidelines, training, data entry quality and resourcing
• May perform quality control of data entry
• Provide input, assesses and manage timelines. Ensure that clinical data management deadlines are met with quality. Assess resource needs for assigned projects, as needed.
• May develop CRF specifications from the clinical study protocol and coordinate the review/feedback from all stakeholders
• Conduct database build UAT and maintain quality controlled database build documentation. Oversee overall quality of the clinical database.
• May specify requirements for all edit check types e.g. electronic, manual data review, edit checks, etc. Oversee development of the edit check specifications and manual data review specifications
• Responsible for creating, revising, appropriate versioning and maintaining data management documentation. Oversee completeness of data management documentation for the Trial Master File.
• Train clinical research personnel on the study specific CRF, EDC, and other project related items as needed.
• Review and query clinical trial data according to the Data Management Plan
• Perform line listing data review based on the guidance provided by the sponsor and/or Lead DM
• Run patient and study level status and metric reporting
• Perform medical coding of medical terms relative to each other in order to ensure medical logic and consistency
• Coordinate SAE/AE reconciliation
• Liaises with third-party vendors such as external data and EDC vendors in a project manager capacity in support of timelines and data-related deliverables
• May assist with SAS programming and quality control of SAS programs used in the Data Management department
• Identify and troubleshoot operational problems, issues, obstacles, and barriers for studies based on metrics data, audit reports, and input from project team members and other stakeholders
• May assist in reviewing and providing feedback on protocols, Statistical Analysis Plans (SAP) and Clinical Study Reports (CSRs), if required by the project
• Participate in the development and maintenance of Standard Operating Procedures (SOPs) and corresponding process documentation related to data management and database management activities
• May attend strategy meetings, bid defense prep meetings, bid defenses, capability presentations, potential client engagement meetings
• May review Request for Proposals (RFP), proposals, provide project estimates
• Provide leadership for cross-functional and organization-wide initiatives, where applicable
• Trains and ensures that all data management project team members have been sufficiently trained
• Communicate with study sponsors, vendors and project teams as needed regarding data, database or other relevant project issues
• May present software demonstrations/trainings, department/company training sessions, present at project meetings
• Perform other duties as assigned

Clinical Data Manager II/Senior Clinical Data Manager

• Our Data Science team works across our entire business, from new products, to core credit decisioning, to user acquisition
• You'll get exposure to a wide range of projects, such as:
• AI & Machine Learning Development: work directly on our proprietary loan decision platform, Render, contributing to the transformer models that allow us to outperform the market in loan performance
• Open Banking Integrations and Classification: enhancing how we transform noisy, real-time transaction data into automated lending decisions
• Product Development: participate in rapid feature development cycles, with direct impact on customer experience and business outcomes
• Bi-annual technical reviews and career progression planning
• Cross-functional exposure to risk, compliance, underwriting and product teams

Graduate Data Scientist

Senior Clinical Data Manager

• Through your own investigation, to become an expert in Relay marketplace pricing dynamics, using it to define how routes are priced.
• To build and maintain production models that inform the daily pricing decisions.
• To experiment and measure the impact of model improvements or pricing strategy changes.

Senior Data Scientist – Last Mile Pricing

• Contribute to the development of machine learning solutions from design through to deployment
• Build and evaluate predictive models using Python and SQL
• Translate business challenges into structured data science problems
• Conduct statistical analysis and feature engineering to generate actionable insights
• Support A/B test design, evaluation, and interpretation with rigour and clarity
• Collaborate with stakeholders to ensure data science solutions are well aligned to product and business needs
• Work with ML Engineers to support deployment, monitoring, and performance tracking of your models
• Contribute to team standards on reproducibility, documentation, and model evaluation
• Apply responsible AI practices to ensure fairness and transparency
• Take part in peer reviews, knowledge sharing, and internal learning sessions
• Support and coach junior team members and peers, contributing to their growth
• Play an active role in shaping our data science culture and community

• Diagnose and improve our data stack in your first 12 months. Propose a target architecture against our goals of AI-native self-serve-first analytics (warehouse, modelling, semantic layer, BI, exploration). Replace tools where needed
• Design and own the acquisition data integration playbook. Build a canonical Lawhive data model that future systems map to. Make firm onboarding a repeatable weeks-not-months process
• Make Lawhive self-serve on data. Build the platform, modelling, and semantic layer that lets business users explore, drill in, and answer their own questions
• Define and enforce data quality SLAs. Freshness, accuracy, ownership coverage, end-to-end lineage
• Lead and grow the data team. Coach analysts into stronger cross-functional partners. Hire and onboard a data integration engineer in year 1
• Partner with Strategy on metric definition. You own instrumentation, semantic layer, and accuracy. They own the metric tree. Together you run the metric council
• Drive AI-native practices inside the data function. Use LLMs for entity resolution, schema mapping, data quality, and exploration. Set the bar for how a data team works in 2026
• Be a key cross-functional partner to Product, Engineering, Finance, Strategy, and the operational teams within acquired firms

• Develop and own a cohesive strategy for Data, Digital and Market Intelligence within Marketing, aligned to First Intuition’s commercial priorities and growth ambitions
• Lead horizon scanning for digital marketing and data trends - including AI, machine learning and personalisation tools - to identify opportunities for innovation and continuous improvement
• Act as the senior advisor to the Director of Marketing and wider leadership on data, digital and technology opportunities, risks and investment decisions
• Drive a culture of curiosity, evidence based decision-making and analytical thinking across the Marketing function
• Lead the development of marketing data capabilities, ensuring strong governance, accuracy, compliance and accessibility for decision-making
• Work with FI Insights to integrate marketing data into the data lake and evolve central tools to support robust reporting, segmentation and market intelligence
• Build frameworks for customer segmentation, behavioural insights, commercial performance analysis, customer satisfaction and journey optimisation
• Ensure insights and analytics deliver actionable recommendations that support proposition development, campaign optimisation and market prioritisation
• Maintain high standards of data integrity and statistical robustness across all marketing reporting and analysis
• Oversee marketing’s digital estate - including websites, content management systems, analytics tools and digital marketing technologies - to ensure effectiveness, stability and user experience excellence
• Partner closely with IT and external agencies to maintain a robust and secure infrastructure and deliver continuous improvements
• Support the evolution of digital tools to enhance personalisation, automation, learner journeys and marketing performance
• Lead digital performance reporting and insight generation to improve conversion, engagement and digital ROI
• Lead a market intelligence function that delivers true value for First Intuition - identifying key trends, opportunities, risks and competitive dynamics to inform First Intuition’s commercial strategy
• Deliver structured market, sector and competitor insight to support decision-making by marketing and Senior Leadership
• Leverage internal and external data to produce fully rounded insight narratives that support growth, new product development and market prioritisation
• Own regular insight outputs such as dashboards, commercial reporting suites and strategic commentary
• Own all marketing technology (HubSpot marketing modules, marketing automation, analytics platforms, website CMS, integrations), ensuring tools are fit for purpose and support the needs of the business
• Lead supplier and agency relationships, contracts and budgets to maximise value and ensure strong performance
• Develop clear processes for technology utilisation, governance and best practice across marketing
• Ensure CRM and associated data flows are effectively managed, integrated and optimised for reporting and insight
• Build, lead and develop the Data, Digital & Market Intelligence team in line with growth plans
• Inspire excellence across analytics, digital practices and data-driven marketing within the wider Marketing team
• Ensure strong project management discipline across all programmes of work, delivering to time and budget

Head of Data, Digital & Market Intelligence

• Analysing large datasets using tools such as SQL, Python, and Radar to support pricing and underwriting decisions
• Supporting the development of data assets and models, contributing to improved risk assessment and pricing accuracy
• Producing clear insights and analysis, and communicating findings to both technical and non-technical stakeholders
• Collaborating with Retail Pricing and Platform teams to support the release of platform and pricing changes
• Contributing to experiments and analysis, helping to test ideas and quantify their potential impact (with guidance from more senior colleagues)
• Supporting the delivery of projects, working with more experienced team members to ensure high-quality and timely outcomes

See all jobs on JobTailor

Senior Lead Clinical Data Science Programmer

Senior Data Scientist – Telematics

Data Scientist

Data Scientist II

Product Data Scientist

Senior Data Scientist

Head of Data

Data Scientist

Trading Data Science Graduate

Senior Data Scientist

Senior Data Science, Analytics Lead

Data Scientist – Agentic AI

Clinical Data Manager II/Senior Clinical Data Manager

Graduate Data Scientist

Senior Clinical Data Manager

Senior Data Scientist – Last Mile Pricing

Data Scientist

Head of Data

Head of Data, Digital & Market Intelligence

Motor Data Scientist