1 to 25 of 79 Statistical Modelling Jobs in the South East

modeling, predictive analytics, and computational intelligence to analyze complex systems, support strategic decision-making, and optimize sustainability outcomes. Responsibilities include, but are not limited to: Develop advanced mathematical and statistical models to support data-driven insights and decision-making. Design and implement predictive and prescriptive analytics frameworks to assess and forecast key trends. Apply AI and machine learning techniques … enhance analytical methodologies. Qualifications and Skills: Master’s or Ph.D. in Mathematics, Data Science, Statistics, Environmental Science, AI, Computational Modeling, or a related field. Strong expertise in mathematical modeling, statistical analysis, and computational techniques. Proficiency in AI and machine learning algorithms, particularly in predictive modeling and data-driven decision-making. Experience with programming languages such as Python, R, MATLAB … or similar for data analysis and modeling. Familiarity with sustainability frameworks and SDGs and experience in sustainability data analytics. Ability to work with large datasets and apply statistical inference and probabilistic modeling. Strong analytical and problem-solving skills with a keen understanding of complex systems. Excellent communication skills to translate technical insights into actionable recommendations. Desirable: Experience with geospatial More ❯

similar analytics role (gaming, betting, or consumer apps is a big plus) Strong skills in SQL, Python or R, and data visualisation tools (e.g., Tableau, Power BI) Experience with statistical analysis, predictive modelling, and segmentation techniques Understanding of user behaviour analytics, retention metrics, and A/B testing Bonus: Experience with fraud detection or risk analytics Strong attention More ❯

working in a growing team, and who loves sport. What you’ll do: Lead data science workstreams on client projects, managing analysts and collaborating with consultants. Develop and deploy statistical models and core IP. Build reusable tools to streamline analysis and visualisation. Communicate insights clearly to all audiences. Mentor junior team members and support capability growth. Work with engineers More ❯

out more about us by visiting our website at: http://www.hartreepartners.com/ROLE OVERVIEW: Hartree Partners is growing its data-driven analytics team and is hiring a Statistical Data Scientist to sharpen our view of weather-driven risk and support wider supply-and-demand modelling for power & gas trading. You will play a pivotal role in … shaping our data strategy and driving the development of our modelling approaches. You will collaborate with cross-functional teams to design, implement, and optimize data pipelines and predictive models that inform trading decisions and enhance operational efficiency. RESPONSIBILITIES: Primary Focus: Probabilistic Weather Modelling: Research and prototype probabilistic methods (Bayesian inference, state-space filtering, change-detection tests, etc.) that … based on real-time data and feedback from trading activities. Model Communication: Explain uncertainty clearly, turning numbers into concise narratives and action-oriented alerts Broader Contributions: Build and refine statistical/ML models for short- to medium-term demand, renewables output, and other fundamental time series. Help design feature pipelines, scenario tools and model-performance dashboards used daily by More ❯

in a clear and concise manner. Requirements: • Master's or PhD degree in a quantitative field. • Proven experience of large-scale data analysis and hypothesis testing. • Strong proficiency in statistical analysis and predictive modeling. • Proficient in Python (pandas, scipy, numpy, scikit-learn) or R (tidyverse/data.table), along with SQL. • Excellent problem-solving skills and attention to detail. • Strong More ❯

to deliver value-adding projects. Foster team growth and prepare members for career advancement. Analyse company performance metrics to guide and interpret models. Shape the R&D strategy and modelling roadmap. Assist in acquiring vendor data and develop arguments. Provide expert mentorship for ongoing and new pricing activities. Design experiments and multivariate testing for AI evaluation. Assess machine learning … solutions for feasibility and operationalize successful prototypes with Data Engineers. Use statistical techniques to optimise business performance. Develop and maintain algorithms to improve customer value and services. Deliver data science projects that drive business benefits and competitive advantage. Conduct ad-hoc analysis to predict, measure, and interpret business trends. Mentor data scientists and champion standard processes within the analytics … years as a Data Scientist in commercial or R&D environments. PhD or MSc or equivalent experience in a relevant field (Machine Learning, Computer Science, Statistics). Experience applying statistical and machine learning models to real-world problems with measurable results. Leadership experience within a high-performing team, including mentorship and management readiness. Proven track record to take research More ❯

to deliver value-adding projects. Foster team growth and prepare members for career advancement. Analyse company performance metrics to guide and interpret models. Shape the R&D strategy and modelling roadmap. Assist in acquiring vendor data and develop arguments. Provide expert mentorship for ongoing and new pricing activities. Design experiments and multivariate testing for AI evaluation. Assess machine learning … solutions for feasibility and operationalize successful prototypes with Data Engineers. Use statistical techniques to optimise business performance. Develop and maintain algorithms to improve customer value and services. Deliver data science projects that drive business benefits and competitive advantage. Conduct ad-hoc analysis to predict, measure, and interpret business trends. Mentor data scientists and champion standard processes within the analytics … years as a Data Scientist in commercial or R&D environments. PhD or MSc or equivalent experience in a relevant field (Machine Learning, Computer Science, Statistics). Experience applying statistical and machine learning models to real-world problems with measurable results. Leadership experience within a high-performing team, including mentorship and management readiness. Proven track record to take research More ❯

on a wide range of actuarial-related areas. The Role As a Machine Learning Engineer you will: Model development. Work collaboratively with actuarial analysts to develop machine learning and statistical models to predict outcomes, related to pension schemes, such as life expectancy, default risk, or investment returns. Identify appropriate machine learning algorithms and apply them to enhance predictions, automate … decision-making processes, and improve client offerings. Machine Learning Operations. Responsible for designing, deploying, maintaining and refining statistical and machine learning models using Azure ML. Optimize model performance and computational efficiency. Ensure that applications run smoothly and handle large-scare data efficiently. Implement and maintain monitoring of model drifts, data-quality alerts, scheduled r-training pipelines. Data Management and … quality. Software Development. Write clean, efficient and scalable code in Python. Utilize CI/CD practices for version control, testing and code review. Work closely with actuarial analysts, actuarial modelling team (AMT) and other colleagues to integrate data science findings into practical advice and strategies. Stay abreast of new trends and technologies in Data Science technologies and pensions to More ❯

ML frameworks/libraries (e.g., TensorFlow, PyTorch, scikit-learn). Strong grasp of LLMs, GenAI, and AI system architectures. Experienced with large-scale datasets and preprocessing pipelines. Skilled in statistical modelling and data visualization tools (e.g., Tableau, Seaborn, Matplotlib). Able to independently lead complex projects from design to deployment. Desirable: Experience with big data tools (Hadoop, Spark More ❯

deploying machine learning models that enhance our consulting capabilities and client offerings. Day-to-day of the role: Model Development: Collaborate with actuarial analysts to develop machine learning and statistical models for predicting outcomes related to pension schemes. Utilize appropriate algorithms to enhance predictions and automate decision-making processes. Machine Learning Operations: Design, deploy, maintain, and refine statistical More ❯

and how they operate Extensive experience designing, developing and maintaining pipelines and tools to measure real-time engineering operations and processes Strong analytical and problem-solving skills in performing statistical analysis, data modeling, and predictive analytics. Professional experience in modern C++, including the STL and common testing frameworks Fluency in Python for software development Ability to develop high-quality More ❯

. Understanding of Gen AI models, Vector databases, Agents, and follow the market trends. Its desirable to have a hands-on experience on these. Substantial experience using tools for statistical modelling of large data sets Some familiarity with data workflow management tools such as Airflow as well as big data technologies such as Apache Spark or other caching More ❯

Be Doing: Work closely with fellow data scientists to explore how AI/ML can unlock insights and improve decision-making. Perform advanced analysis on large, complex datasets using statistical and modelling techniques. Build, test, and tune ML models (especially NLP or computer vision) using Python and modern ML libraries, all within Google Cloud Platform (GCP) . Optimise More ❯

and 3rd party panels to test fast-evolving hypotheses. Design and automate reporting processes , bringing visibility to crucial metrics and freeing teams to act on what matters most. Build statistical models and algorithms to detect patterns and opportunities for optimisation. Create compelling data visualisations using Grafana and Power BI to track performance in real time. Communicate complex analytical findings … across the business. YOUR SKILLS AND EXPERIENCE: The ideal Senior Data Analyst will have: Proficiency in Python or R , with hands-on experience building analytical models. Strong knowledge of statistical techniques , from regressions to machine learning algorithms. Excellent SQL and data manipulation skills , with experience working on large, complex datasets. Familiarity with cloud data platforms such as AWS, Azure More ❯

data analysis techniques and tools to deliver actionable customer intelligence efficiently. Collaborate with business units to provide a comprehensive understanding of the customer base and quantify commercial opportunities. Utilise statistical models to understand customer risk, value, and behaviour, ensuring effective use in marketing campaigns. Identify data quality issues and suggest improvements to data structures, while project managing detailed analysis … programmes. What do I need? Degree within a STEM subject and/or proven demonstrable equivalent working experience within data/insight analytics, data mining and statistical techniques. Proficient in SQL; knowledge of Python/Databricks/R is desirable. Demonstrable competence in delivering actionable customer intelligence. Strong analytical, decision-making, and problem-solving skills. Ability to translate complex More ❯

which has not previously been obtainable. The Role: Data Cleaning and Preparation: Collect, clean, and prepare large media datasets from various sources (CRM, ad servers, audience panels) for analysis. Statistical Analysis: Utilise econometric techniques like regression analysis, time series modelling, and panel data analysis to identify relationships between media spend and business outcomes. Model Validation and Interpretation: Evaluate … learning to enhance model accuracy and uncover deeper insights. Your Experience and Skills: Data Science: Proficient in programming languages like Python, R, and SQL including data manipulation, data imputation, statistical modelling, and visualisation libraries. Expertise in statistical methods like linear regression, generalised linear models, panel data analysis, and time series forecasting. Media Industry Knowledge: Understanding of media … landscape, ad formats, audience measurement, and industry KPIs. Communication Skills: Ability to clearly communicate complex statistical concepts and insights to non-technical stakeholders. Business Acumen: Understanding of business objectives and ability to translate data insights into actionable strategies. Additional Skills: Build and maintain complex MMM models to assess the incremental impact of different media channels (TV, digital, print) on More ❯

keeping abreast of upcoming change, or areas for improvement Grow the impact of Data Science across the Group, increase the number of deployed solutions, identify previously unexplored areas of modelling or analysis Role model best practice, with focuses on efficiency and long term success Monitor the latest techniques and solutions being utilised in the wider industry Maintain departmental risk … and guidelines and other relevant standards/regulations at all times. Any other reasonable duties Experience & knowledge Extensive hands-on experience applying data science techniques to general insurance predictive modelling problems Strong track record of stakeholder management, modelling projects and successful deployment Deep understanding and familiarity with a variety of statistical models (eg GBMs, GLMs, clustering techniques … change framework Strong technical leader, able to recruit and develop a strong team Good communication skills, both verbal and written Good time management and organisation skills Proven analytical and statistical modelling skills Degree in Data Science or other quantitative field Behaviours Self-motivated and enthusiastic with the desire to meet or exceed targets Determined and passionate, particularly regarding More ❯

Company Overview: My client is a leading quantitative trading and investment firm that researches, develops, and deploys algorithmic trading strategies across global markets. Their team leverages advanced mathematical models, statistical techniques, and cutting-edge technology to trade across all asset classes on multiple exchanges worldwide. Role Overview: They are seeking a highly analytical and driven Commodity Trader to join … or algorithmic environment. Strong programming skills in Python, C++, or similar languages used in quantitative research. Deep understanding of commodity markets, including futures, options, and spot trading. Experience with statistical modelling, machine learning, or signal processing techniques. Familiarity with market microstructure and electronic trading platforms. More ❯

heart of the energy sector to design, develop and operate a greener, net zero future for Great Britain! This is an exciting opportunity to join the ‘Frequency Risk and Modelling’ team who are responsible for providing analytical and model development to ensure frequency security of the GB system. The team sets out policy and optimises requirements for the procurement … control agreements and obligated to identify optimal solutions to system operations and planning in the most sustainable, affordable and secure way for all. Key Accountabilities · Develop, maintain and update Statistical/Machine Learning models and algorithms to generate current and future frequency response and reserve requirements. Coordinate with different functional teams to implement models and monitor outcomes. · Propose operability … solve operational challenges in frequency control. Represent NESO in collaboration with industry and academia. · Support post-event analysis following frequency events in the GB to ensure compliance and drive modelling and process improvement. · Communicate the market change impacts to NESO Senior Management, Ofgem, DESNZ, service providers and other non-technical audiences. About you We’re forging the path, and More ❯

or industry! Knowledge of trial site operations and study execution Strong knowledge of regulatory guidelines (e.g., ICH-GCP). Demonstrated strong understanding of data analysis and familiarity with basic statistical concepts and hands-on experience using data visualization tools Project, Issue, and risk management experience with strong ability to apply critical thinking & problem-solving skills, to drive solutions &helping … drug development processes Preferred Experience Working with complex data structures and reporting specifications Working with external data e.g., Safety Lab, PK, Simple Biomarkers, ECG, or similar. Possess proficiency in statistical analysis, data modelling, and data visualization techniques, or demonstrate strong knowledge in these areas. Strong Knowledge of Monitoring and Risk-based Quality Management (RBQM)/Risk-Based Monitoring More ❯

emerging digital trends in social care. What Were Looking For 34+ years' experience in data analysis, preferably with exposure to health or social care environments. Proven ability to conduct statistical modelling, indicator development and create powerful visualisations. Experience handling large, complex datasets (structured and unstructured) using tools like Power BI, SQL, R, Python or Tableau. Comfortable using qualitative More ❯

science methods for measuring the quality of health and social care services, learning from best practice (national/international), both internally and externally. Assess the effectiveness of different advanced statistical and data science modelling approaches and advise data scientists on best tools and approaches to support organisational commitments. Manage competing demands for Data Science work within the Data More ❯

technical methods in plain English Great attention and care for detail Self-starter attitude: proactive, resourceful, and eager to learn new technologies Future Focus Exposure to machine learning or statistical modelling libraries Familiarity with the Greenhouse Gas Protocol and basic carbon-accounting principles What We Offer Starting salary £30 – 35k, with opportunity for role progression We’re a More ❯

Data Scientist (Loss Modelling) Hybrid (London – 3 days on-site) Series A Impact Tech Business £60k - £80k + Meaningful Equity Albany Growth are partnering with a mission-led impact tech focused company backed by a top-tier VC who are looking to expand out their world class research and science team and as a result are looking for a … Data Scientist with specific experience in loss modelling . This role is ideal for someone with experience in catastrophe or physical risk modelling, applied statistics, and geospatial data. You’ll play a key role in shaping the loss modelling framework behind a next-generation SaaS platform used by global clients across banking, insurance, and real estate. Key … scientifically grounded loss models across things such as floods, storms, droughts, and wildfires Calibrate and validate models using large geospatial and financial loss datasets Help shape a flexible loss modelling framework adaptable across global markets Collaborate with stakeholders to communicate modelling approaches and outputs Represent the team at industry events and contribute to external engagement Key Requirements Strong More ❯

VC who are looking to expand out their world class research and science team and as a result are looking for a Data Scientist with specific experience in loss modelling . This role is ideal for someone with experience in catastrophe or physical risk modelling, applied statistics, and geospatial data. You’ll play a key role in shaping … the loss modelling framework behind a next-generation SaaS platform used by global clients across banking, insurance, and real estate. Key Responsibilities Develop and implement robust, scientifically grounded loss models across things such as floods, storms, droughts, and wildfires Calibrate and validate models using large geospatial and financial loss datasets Help shape a flexible loss modelling framework adaptable … across global markets Collaborate with stakeholders to communicate modelling approaches and outputs Represent the team at industry events and contribute to external engagement Key Requirements Strong experience in catastrophe or loss model development and calibration Applied statistical background with ability to validate models both quantitatively and qualitatively Proficiency with geospatial data , Earth Observation sources, and climate datasets Skilled More ❯