complex calculations, custom visualizations, and performance optimization. •SQL Development Skills: Mastery of SQL, including the ability to write complex queries, stored procedures, views and perform query optimization. •Programming/Statistical Analysis Skills: Working knowledge of R or Python for analytics, data manipulation, and algorithm development. •Data Warehousing Knowledge: In-depth knowledge of data warehousing principles, dimensional modeling techniques (e.g. … project management methodologies (e.g., Agile, Waterfall) and tools (e.g., JIRA, Confluence). PREFFERED QUALIFICATIONS •Minimum 1+ years of experience supporting a Financial Operations function •Experience in advanced data analytics, statistical modeling, and predictive analytics using tools such as Alteryx, Python, or R; experience with machine learning algorithms and techniques is a plus. •Experience in building and maintaining APIs for More ❯
crime across the NHS. Further information about our work and annual plan for delivering this is available on our website. The Data Scientist role requires expertise in machine learning, statistical analysis, anomaly detection, and strong communication and collaboration skills. Key responsibilities include developing innovative models, designing, applying, and optimising models in a dynamic environment. The role is critical in … project planning, using data to drive business objectives, and defining project directions to achieve financial targets. With a deep understanding of data science, including machine learning, predictive modelling, and deep learning, the Data Scientist will tackle complex challenges and extract actionable insights from diverse datasets. They will lead model development and ensure solutions meet business and government standards. The … NHSCFA goals, ensuring accountability for innovative outcomes. Utilising the latest advanced methods, they will embed analytics into the organisation to enhance fraud detection within the NHS. Clear communication of statistical outputs and results to non-technical stakeholders is crucial, influencing decisions like criminal intervention, policy changes, or risk metrics based on data-driven insights. The role demands adherence to More ❯
and financial institutions, plan their strategies and future investment with a reliable, consistent and complete understanding of the global landscape. Role Overview: IWSR is expanding its Forecasting, Analytics and Modelling capabilities and seeks a Data Scientist as part of its growing team of data scientists and econometricians. This team is responsible for the production of forecasts and analyticsin collaboration … and modelling. Key Responsibilities: 1. Elevate Forecasts, Analytics, and Models Ensure IWSR's forecasts, analytics, and models are market-leading in quality, relevance, and reliability Approach forecasting, analytics, and modelling challenges with rigor, adaptability, and creativity. 2.Data Analysis and Exploration Support the collection, cleansing, and analysis of data from diverse sources Identify trends, patterns, and actionable insights to drive … decision-making and solve complex business problems. 3. Statistical & Mathematical Modelling and Machine Learning/AI Support the development ofpredictive models, to forecast trends and outcomes Support the development and implementation of machine learning algorithms to address specific business challenges Collaborate with the team to deploy, run, and maintain models in a production environment Evaluate and fine-tune More ❯
of intricate business challenges and translation into technical problem statements. o Working with diverse datasets, both internal and external. o Expert application and development of advanced machine learning or statisticalmodelling techniques to generate actionable insights and deliver measurable impact. • Provide hands-on technical mentorship and guidance to junior and mid-level data scientists, fostering best practices, elevating … Skills: • Exceptional proficiency in Python (and R) for data science, coupled with SQL capabilities for data manipulation and extraction. • Demonstrable mastery in a wide range of machine learning and statisticalmodelling techniques, from classical linear models and tree-based methods to advanced deep learning architectures. • Practical experience with, or demonstrable capability for, applications of Generative AI, Large Language More ❯
campaign effectiveness. You'll be part of a collaborative, technically skilled team that combines deep analytical thinking with commercial understanding to solve complex marketing challenges using machine learning and statistical modelling. Key Responsibilities Advanced Analytics & Modelling Design and implement machine learning algorithms and statistical models tailored to the marketing domain Apply techniques such as segmentation, uplift modelling … marketing analytics or a clear passion to grow in this domain Proficiency in Python and SQL (a technical test is part of the process) Solid understanding of machine learning, statisticalmodelling, and experimentation Strong communication skills to engage with business teams and explain complex concepts clearly Experience working with cloud platforms and big data tools, preferably Azure A More ❯
responsibility will be to harness the power of data to extract meaningful insights, inform strategic decisions, and contribute to the overall success of the organisation using machine learning and statistical techniques. You will have access to the latest analytical tools and the chance to work with some of the most renowned Decision Data leaders in the UK market. We … leave Grandparents leave Income protection Access to Saga Academy, our bespoke learning platform Main Responsibilities Our Senior Data Scientist will be fully accountable for the following areas; Advanced Analytics & Modelling: Design, develop, and implement advanced machine learning algorithms and statistical models to solve complex business problems. Drive the exploration and adoption of cutting-edge data science techniques and … demonstrate strong programming skills in languages such as Python and SQL. (A technical task will form part of the interview process.) Already be a credible expert in machine learning, statisticalmodelling and data analysis. Demonstrate excellent communication skills with the ability to convey complex technical concepts to both technical and non-technical stakeholders providing business recommendations within a More ❯
mentoring other scientists, engineers in the use of ML techniques BASIC QUALIFICATIONS - 5+ years of data scientist experience - Experience with data scripting languages (e.g. SQL, Python, R etc.) or statistical/mathematical software (e.g. R, SAS, or Matlab) - Experience with statistical models e.g. multinomial logistic regression - Experience in data applications using large scale distributed systems (e.g., EMR, Spark More ❯
are relevant to our work, they are not strict requirements: BS or MS degree in Data Science, Statistics, Computer Science, or a related field. Proven experience in machine learning, statistical modeling (5+ years) Proficiency in programming languages such as Python or R. Experience with SQL and working with large datasets. Strong expertise in designing and building robust data pipelines More ❯
translating complex data into comprehensive analysis under tight deadlines. Perform advanced data analysis, including feature engineering and modeling. Cleanse, integrate, and analyze diverse datasets for insights. Conduct hypothesis testing, statistical analysis, and modeling. Create and manage a roadmap for analysis improvements and new insights. Incorporate feedback from investment teams to enhance diligence outcomes. Collaborate with data and insight teams … skills, including presentation and storytelling. Knowledge of investment, valuation, and growth principles. Advanced Python and SQL skills. Experience with machine learning and large datasets. Skills in data visualization and statistical modeling. Familiarity with AWS and Git. Company Information The Carlyle Group (NASDAQ: CG) manages $453 billion in assets, with a diverse global presence and a commitment to inclusion and More ❯
clean, and analyse large and complex payment data sets from diverse sources Identify trends, patterns, and anomalies within the data to uncover insights. Utilise advanced data analysis techniques (e.g., statisticalmodelling, machine learning) to extract meaningful information. Insight Generation: Develop comprehensive reports, dashboards and visualisations to communicate findings to stakeholders. Provide detailed analysis including creation of financial models … degree in Finance, Accounting, Economics, or a related field. Advanced knowledge of data analysis tools (e.g., SQL, Python, R). Strong analytical and problem-solving skills. Proficient in financial modelling, budgeting and forecasting. Experience working with large and complex data sets. Excellent communication and interpersonal skills. Ability to translate technical findings into clear and actionable recommendations. Not necessary but … would be desirable to have: Master's degree in Data Science, Statistics, or a related field. Experience in Virtual card payments and rebate structures. Knowledge of machine learning and statisticalmodelling techniques. Experience with data visualisation tools (e.g., Looker, Power BI, Google Suite). Perks of joining us: Other than an amazing environment for you to grow, have More ❯
Location. Purpose of the role To provide quantitative and analytical expertise to support trading strategies, risk management, and decision-making within the investment banking domain, applying quantitative analysis, mathematical modelling, and technology to optimise trading and investment opportunities. Accountabilities Development and implementation of quantitative models and strategies to derive insight into market trends and optimize trading decisions, pricing, and … risk management across various financial products and markets. Working closely with sales teams to identify clients' needs and develop customised solutions. In-depth research, data analysis, and statisticalmodelling to derive insights into market trends, pricing, and risk dynamics. Provide front office infrastructure support though ownership and maintenance of analytical libraries. Provision of expertise on quantitative methodologies, technological More ❯
large datasets from various sources to uncover insights and patterns. Collaborate with cross-functional teams to understand business objectives and translate them into new data products Perform data mining, statistical analysis, and predictive modelling to drive business decisions. Build data architecture and pipelines to support data products Build predictive models for various business applications (e.g., Research Pricing, recommendation … technical and non-technical stakeholders. Knowledge, Skills and Experience Required Minimum of 3 years of hands-on experience in data product development. Strong understanding of data structures, algorithms, and statistical concepts. Proficiency in Python and ETL frameworks Deep knowledge of data pipeline architectures and products such as Snowflake or similar Experience with delivering data products to clients via APIs More ❯
Experience monitoring and optimizing model performance in production settings. Programming Languages: Strong coding skills in Python and SQL. Experience with Node.js, JavaScript (JS), and TypeScript (TS) is a plus. Statistical Knowledge: Solid understanding of statistical concepts and methodologies for analyzing and interpreting large datasets. Ability to apply statistical techniques to validate models and algorithms. Data Manipulation & Analysis 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 ❯
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 ❯
the opportunity of working in a growing team, and who loves sport. Responsibilities: 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 ❯
the opportunity of working in a growing team, and who loves sport. Responsibilities: 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 ❯
years of business or financial analysis experience - Experience defining requirements and using data and metrics to draw business insights - Experience making business recommendations and influencing stakeholders - Strong proficiency in statistical analysis and modeling (R, Python) - Experience with regression analysis and correlation modeling - Knowledge of financial modeling and P&L analysis - Familiarity with machine learning concepts - Proficiency in SQL and More ❯
s strategy. We are looking for a well-established Data Scientist at all levels who wants new challenges. As a Senior Data Scientist, you will work using data engineering, statistical, and ML/AI approaches to uncover data patterns and build models. We use Microsoft tech stack, including Azure Databricks (Pyspark, python), and we are expanding our data science … to work closely with business stakeholders, data engineers, marketing analysts and BI analysts to improve our existing models, create new models, and bring our expertise. Core Responsibilities Apply advanced statistical techniques and ML/AI models to development and production environments Collaborate with team members and stakeholders to build data science products that enable others to make business decisions … Qualifications Postgraduate degree in a relevant discipline (e.g. STEM, Maths, Statistics, Physics) or equivalent experience Good data modelling, software engineering knowledge, and strong knowledge of statistical, mathematical and ML modelling are a must at this stage. Skilful in writing well-engineered code Proven experience working with ML engineers and production systems (including Cloud platforms) Proven ability to More ❯
Ago time left to apply End Date: June 27, 2025 (7 days left to apply) job requisition id JR0024 What will you be doing day-to-day? Use sophisticated statistical and machine learning techniques to identify new trends and relationships in data. Harvest, wrangle and prototype new data sources internally and external to NewDay to create new value for … procedures and standards. Your Skills and Experience ESSENTIAL At least a BSc or higher university degree in a data science related field (e.g. machine learning, statistics, mathematics) Proficiency in statistical data modelling techniques. Proficiency with Python, including experience with statistics/machine learning packages such as scikit-learn, pandas, numpy, etc. Good SQL/data manipulation skills required … Honest and hardworking with a will to learn as well as develop others. Strong sense of accountability and ownership, with great organizational, planning and time management skills. Passionate about modelling and techniques to drive value from data. Personable with excellent interpersonal & written communication skills. Ability to build strong and effective working relationships with people across all levels of the More ❯
and drive improvements in pension provision. You will work closely with business owners to identify opportunities to drive value from data and lead the development of advanced analytics & predictive modelling algorithms. You will be comfortable working independently and as part of small teams in dynamic projects across Just to develop predictive models, identify health and mortality trends, and implement … new technologies Good understanding of Microsoft Server technologies (Azure, T-SQL, SSIS, SSRS, Power BI) Experience Strong experience of working as a Data Scientist or equivalent role, in applying statistical models and machine learning algorithms Experience and ability to respond to business needs by identifying appropriate statistical methodologies and presenting insight for decision making Attention to detail & problem 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 ❯
applied research to production is a must - Excellent problem solving and data analysis skills and a good grasp of applied statistics. Particularly, expertise in developing or applying predictive analytics, statisticalmodelling, data mining, or machine learning algorithms, especially at scale - Strong people leadership skills to influence others, with the ability to tech-lead, understand team dynamics, retain, attract More ❯
applied research to production is a must Excellent problem solving and data analysis skills and a good grasp of applied statistics. Particularly, expertise in developing or applying predictive analytics, statisticalmodelling, data mining, or machine learning algorithms, especially at scale Strong people leadership skills to influence others, with the ability to tech-lead, understand team dynamics, retain, attract More ❯
into specific plans for engineering teams. Design and execute machine learning projects/products end-to-end: from ideation, analysis, prototyping, development, metrics, and monitoring. Drive end-to-end statistical analysis that have a high degree of ambiguity, scale, and complexity. Research and develop advanced Generative AI based solutions to solve diverse customer problems. BASIC QUALIFICATIONS - 2+ years of … data scientist experience - 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience - 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience - Experience applying theoretical models in an applied environment - Experience applying various machine … cause and effect relationships. Have a history of building systems that capture and utilize large data sets in order to quantify performance via metrics or KPIs. Understanding of relevant statistical measures such as confidence intervals, significance of error measurements, development and evaluation data sets, etc. PREFERRED QUALIFICATIONS - Experience in Python, Perl, or another scripting language - Experience in a ML More ❯
