1 to 25 of 27 Predictive Modelling Jobs in the City of London

analytics solutions that drive measurable business outcomes. Reporting directly to the Director of Data, you’ll take ownership of high-impact projects across areas such as customer lifetime value, predictive modelling, bidding optimisation, and experimentation, whilst also acting as a data lead for major clients. Initially hands-on, this role will evolve into a more strategic leadership position … team management responsibilities (starting with three Data Scientists, growing to five within a year) expected within the first six months. Key Responsibilities Lead and deliver data science solutions across predictive modelling, optimisation, and experimentation. Act as a strategic data partner to key clients, owning technical delivery and ensuring high-quality results. Design and deploy machine learning models and … algorithms into production. Solid understanding of digital marketing concepts, platforms (e.g., Google Ads, Meta), and analytics tools. Demonstrated experience across key use cases such as: Customer Lifetime Value (CLV) modelling Propensity scoring and lead prioritisation Budget allocation and bidding optimisation Experimentation, A/B testing, causal inference, MMM Advanced analytics (e.g. marginal returns curves, supply-demand modelling) Strong More ❯

high-impact work across paid media, measurement, and advanced analytics. They operate at the intersection of marketing and data science – with a track record of developing sophisticated experimentation and predictive modelling solutions for major UK brands. This isn’t short-term agency work — they partner closely with clients, often with direct access to raw data and a strong … seat at the strategy table. THE ROLE: As a Senior Data Scientist, you’ll play a key role in leading the delivery of analytics projects across experimentation and predictive modelling. You’ll work directly with clients, helping them answer complex marketing questions and improve performance using robust, data-led methods. This role comes with significant autonomy — you’ll lead … responsibilities include: Own end-to-end delivery of data science projects across marketing measurement and advanced analytics Design and implement experiments (incrementality, geo testing, brand lift, causal inference) Build predictive models (LTV, propensity, pricing) using Python and SQL in a cloud environment Translate complex outputs into clear, strategic recommendations for clients Contribute to internal R&D and shape best More ❯

the intersection of technology, investment, and strategy. Key Responsibilities Translate complex business problems into measurable data science solutions that deliver commercial value Lead the design, development, and deployment of predictive and optimisation models across multiple industries Own the end-to-end ML pipeline: data exploration, feature engineering, modelling, evaluation, and deployment Collaborate with data engineers and MLOps professionals … lead data science projects from concept to production Strong Python skills (including libraries like Pandas, NumPy, Scikit-learn); experience with other languages is a plus Deep understanding of statistical modelling, predictive analytics, and optimisation techniques Comfortable working with cross-functional teams, including engineers, product leads, and client stakeholders Experience with A/B testing and causal inference methodologies … in a quantitative field (e.g., Mathematics, Physics, Engineering, Computer Science) Excellent communication skills and a collaborative mindset Example Projects You Might Work On Optimisation models to increase manufacturing throughput Predictive models for asset maintenance and downtime reduction Customer churn prediction and retention modelling Sales optimisation through next-best-action models Geospatial analysis to inform store or facility network More ❯

MSc/PhD in Data Science, Computer Science, Maths or similar. Hands on experience in data science or AI, including leadership roles. Deep expertise in machine learning, NLP, and predictive modelling. Proficient in Python or R, cloud platforms (AWS, GCP, Azure), and big data tools (e.g. Spark). Strong business acumen, communication skills, and stakeholder engagement. If this role More ❯

and improving performance by reimagining value creation capabilities. They are utilising cutting-edge AI to generate performance insights on each aspect of the investment lifecycle. Responsibilities: Build machine learning predictive models to anticipate/avoid asset downtime and reducing customer churn Evaluate and optimise all models, identifying areas for development Work end-to-end both building and deploying models More ❯

real impact. Responsibilities: Support the investment and deal teams by delivering deep, data-driven insights into potential acquisition targets. Responsible for evaluating market dynamics, identifying growth opportunities, and building predictive models to assess financial and operational performance. Your analysis will play a critical role in shaping investment theses and informing high-stakes decisions on multi-million (and often billion More ❯

Senior Data Scientist to join a mission-driven team building data-driven solutions that improve outcomes in the healthcare sector. In this role, you’ll design, build, and deploy predictive models that harness real-world behavioural data to drive impactful insights. This is a hands-on role ideal for someone who thrives in a collaborative, fast-paced environment and … scale. You’ll work closely with cross-functional teams to operationalize models, support product development, and contribute to a modern MLOps pipeline. What You’ll Do Develop and deploy predictive models using behavioural and real-world data Translate complex datasets into actionable insights that improve healthcare outcomes Contribute to the full ML lifecycle, from data wrangling and feature engineering … into production systems via scalable pipelines Champion best practices in MLOps, including CI/CD for ML, model versioning, testing, and monitoring Design experiments (A/B testing, uplift modelling) to measure impact and optimize performance What We’re Looking For PhD background in a relevant field Proven commercial in data science, with a strong foundation in predictive More ❯

of all forecast models. What we're looking for: Solid academic background in Statistics, Mathematics, Economics, Data Science, or a related discipline A number of years experience in Risk Modelling, Credit Risk, Risk Management Proficiency in statistical tools, preferably Python or R Practical exposure to machine learning, predictive modelling, and advanced analytics techniques Industry experience in Automotive More ❯

culture ✔ Hybrid working with flexible hours and career development support What You’ll Be Doing Analysing operational and performance data from nuclear systems and infrastructure Building dashboards, reports, and predictive models to inform business and engineering decisions Working closely with engineers, scientists, and leadership teams to translate data into action Supporting continuous improvement and regulatory reporting processes Contributing to More ❯

strategies that leverage data science to drive decision-making in investment, trading, and other deeply quantitative domains, aligning with our clients’ business objectives. · Utilize advanced analytics, machine learning, and predictive modeling to interpret market signals and forecast trends, providing clients with a competitive edge. · Strengthen relationships with clients to sustain Accenture’s profile as a long-term trusted advisor More ❯

insight and drive impactful business decisions. Your Responsibilities: Analyse complex datasets: Work with large volumes of financial data to identify trends, patterns, and insights that drive strategic decisions. Support predictive modeling: Collaborate on the development of machine learning models to forecast financial outcomes and optimise business processes. Develop data-driven solutions: Create algorithms and tools that automate and enhance … Mathematics, Computer Science, Engineering, or related fields. Proficiency in programming languages: Experience with Python and SQL for data analysis, manipulation, and modeling. Basic understanding of machine learning: Familiarity with predictive modeling techniques and algorithms, in particular NLP, LLM's and Time Series Forecasting. Experience with data visualisation tools: Knowledge of tools like Tableau/Power BI, or similar to More ❯

healthcare strategies. The Role As a Senior Data Scientist, you will be a key technical leader on their core data products. Your primary focus will be building and deploying predictive machine learning models using large-scale, complex datasets — including consumer data, survey data, and extensive geospatial information. You will take ownership not only of modeling and metric development but … ML Engineer Exposure to behavioral or consumer data is essential, preferably in the Healthcare space Strong Python skills and experience with Databricks or similar platforms Proven track record in predictive modelling with messy, real-world datasets (survey, geospatial, or similar) Hands-on experience with MLOps tools and practices (e.g., MLFlow) and deploying models in cloud environments (GCP, AWS More ❯

team management responsibilities (starting with three Data Scientists, growing to five within a year) expected within the first six months. Key Responsibilities Lead and deliver data science solutions across predictive modelling, optimisation, and experimentation. Act as a strategic data partner to key clients, owning technical delivery and ensuring high-quality results. Design and deploy machine learning models and … algorithms into production. Solid understanding of digital marketing concepts, platforms (e.g., Google Ads, Meta), and analytics tools. Demonstrated experience across key use cases such as: Customer Lifetime Value (CLV) modelling Propensity scoring and lead prioritisation Budget allocation and bidding optimisation Experimentation, A/B testing, causal inference, MMM Advanced analytics (e.g. marginal returns curves, supply-demand modelling) Strong More ❯

This is still a largely hands on role, with around 20% team leadership. What You’ll Do Oversee data science projects, guide junior team members, and drive innovation. Build predictive models for campaign optimisation, customer segmentation, and price elasticity. Design and implement AI-powered solutions to solve complex marketing challenges. Use machine learning and statistical techniques to analyse trends More ❯

This is still a largely hands on role, with around 20% team leadership. What You’ll Do Oversee data science projects, guide junior team members, and drive innovation. Build predictive models for campaign optimisation, customer segmentation, and price elasticity. Design and implement AI-powered solutions to solve complex marketing challenges. Use machine learning and statistical techniques to analyse trends More ❯

grow into a leadership position and shape the future of the data function. THE ROLE: As a Data Scientist in this high-impact team, you’ll: Lead on statistical modelling across a range of quant-led market research and political insight projects. Apply and evolve a robust modelling framework using R , supporting techniques from regression and segmentation through … with the opportunity to build and lead your own team in the near future. YOUR SKILLS & EXPERIENCE We're looking for: Solid Data Science experience in R , especially in predictive modelling and regression/segmentation techniques. Educated to Masters or PhD level A flair for methodological creativity – someone who enjoys being playful and inventive in their approach to More ❯

management systems. Ensure systems meet business requirements and adhere to industry best practises. Develop, implement, automate, and maintain large-scale enterprise data ETL processes. Build high-performance algorithms, prototypes, predictive models, and proof of concepts. Collaborate with data architects, modellers, and IT team members to achieve project goals. Execute plans and policies that control, protect, and enhance the value More ❯

estate firms understand and act on physical climate risk. You’ll define the ML strategy, shape a high-impact team, and deliver real-world innovation across generative AI, geospatial modelling, and time-series forecasting. Key Responsibilities Own and evolve the company’s AI & ML strategy in line with product and customer priorities Lead, mentor, and grow a high-performing … team of ML Engineers Take prototypes through to production, delivering meaningful product features powered by GenAI and predictive modelling Collaborate with Science and Engineering to integrate ML with physics-based climate models Communicate complex technical concepts in simple, outcome-oriented terms for customers and cross-functional teams Your work will focus on delivering high-value insights and solutions … satellite imagery and remote sensing for climate hazard detection Enhancing time-series forecasts to inform asset-level risk planning Combining simulation outputs with ML for hybrid physical + statistical modelling What We’re Looking For Proven leadership and strong hands on experience Proven track record of deploying ML into production environments Depth in at least one of: generative AI More ❯

can enhance product offerings. Design and run experiments to test hypotheses and support product development. Develop robust data pipelines to support science experimentation and production. Deploy, maintain, and monitor predictive models in live environments. Communicate findings and technical concepts clearly to both technical and non-technical audiences. Contribute to agile delivery workflows and cross-functional collaboration. What We’re More ❯

comfortable taking requirements to produce their data insights and reports they need. Future ambitions of the data team are to start investigating trends their existing business data to build predictive models to help the business identify trends, patterns and future insights/events so any experience or interest in this area would be advantageous. Salary is paying up to More ❯

and help shape our customer-centric strategies using data. Key Responsibilities Analyse Customer Behaviour to identify trends in lifetime value (CLV), churn risk, and retention drivers. Build and maintain predictive models for customer retention and churn using statistical and machine learning techniques. Partner with marketing and CRM teams to deliver pre- and post-campaign analytics, including A/B … continuous improvement, innovation, and data-driven decision-making. Skills & Experience Proven experience in a Senior Analyst role, ideally with a focus on customer lifecycle analytics. Strong knowledge of CLV modelling, churn prediction, retention analytics, and campaign performance analysis. Proficiency in SQL. Experience with data visualisation tools such as Tableau, Power BI, or Looker. Solid understanding of A/B More ❯

experience (this can be an internship). This is an exciting opportunity for an early-careers quant with a passion for markets, data, and systematic investing. You will: Develop predictive models for constituent changes and associated flows Analyze historical rebalancing patterns and post-event performance Backtest and validate systematic strategies around index changes Monitor upcoming index events and help More ❯

spanning football, soccer, cricket, and major US sports like the NBA. As part of their elite trading team, you’ll harness advanced statistical techniques and machine learning to build predictive models that shape their trading strategies. In this role, you’ll drive revenue growth and develop mathematical models to predict the outcomes of sports events. Responsibilities: Utilise advanced statistical … techniques and machine learning to build predictive models that shape our trading strategies Develop predictive models for sports outcomes using advanced mathematical and statistical techniques. Analyse real-world sports data to uncover patterns and generate insights that inform trading strategies. Implement and optimise numerical methods to support robust, scalable model performance in live environments. Collaborate closely with fellow … researchers and developers in a fast-paced, science-driven team environment. Continuously innovate and improve modelling approaches to stay competitive in dynamic and data-rich sports markets. Requirements: MSc, PhD Degree in Computer Science, Artificial Intelligence, Mathematics, Statistics or related fields. Strong coding skills in Python and SQL Strong communication skills, with the ability to work effectively in a More ❯

Hiring: Quantitative Analysts – Sports Modelling | London | Up to £130k + Bonus 🚨 A high-performing, close-knit team of researchers and software developers is looking to add Mid-Level and Senior Quantitative Analysts to their growing group. This firm trades on global sports markets using cutting-edge statistical modelling and high levels of automation. 📍 Location: Central London (5 days … a week, with some flexibility) 💰 Salary: Up to £130,000 + 20% Bi-Annual bonus + benefits What you'll do: Build predictive models for sports outcomes (e.g. football, tennis, cricket) Apply rigorous statistical techniques to large real-world datasets Contribute directly to trading strategies in a high-impact, low-bureaucracy setting What we're looking for: MSc/… Maths, Stats, Physics, Computer Science) Strong experience working with real-world data Proficiency in Python (mandatory); R, MATLAB, and C# are a plus Deep understanding of probability, statistics, and modelling Bonus: Genuine interest or background in sports What’s on offer: Flat-structured, non-corporate team culture Exposure to live trading environments and real-time analytics Private healthcare, pension More ❯

technical teams in configuring extraction tools, refining scripts, and ensuring clean data outputs. Data insights – Uncovering key trends in client data and presenting meaningful insights to inform their strategies. Predictive models – Customising existing models to meet client needs and assessing feasibility for new analytics solutions. Cohort analysis – Defining target groups, testing interventions, and iterating approaches based on client feedback. … sector clients, they enable them to proactively address complex societal challenges like financial vulnerability and housing instability. Their approach integrates disparate datasets, applies cutting-edge machine learning, and utilises predictive analytics to pinpoint those most in need. Our platform transforms this information into actionable insights, equipping professionals with the tools to intervene early and drive meaningful change. In the More ❯