Central London, London, United Kingdom Hybrid / WFH Options
Singular Recruitment
Data Scientist, your background will include: 3+ years industry experience in a Data Science role and a strong academic background Python Data Science Stack: Advanced proficiency in Python , including pandas , NumPy , scikit-learn , and Jupyter Notebooks . Statistical & ML Modelling: Strong foundation in statistical analysis and proven experience applying a range of machine learning techniques to solve business problems (e.g. More ❯
the gaming industry is a plus Technical Requirements Advanced/Expert in Excel Advanced in Power BI or similar BI tools Advanced in SQL Intermediate/Advanced in Python (pandas, sklearn) Nice to have: IBM Planning Analytics Job Type: Permanent Location: London, United Kingdom Work Mode: Hybrid Salary: £39,076-£72,571 per year Visa Sponsorship: Not available; candidates must More ❯
industry experience, or an MS with significant industry or research experience in the field • Extensive experience with machine learning and deep learning toolkits (e.g.: TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas) • Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals • Experience with big data and scalable model More ❯
state-of-the-art areas (e.g. NLP, Transfer Learning) and modern Deep Learning algorithms (e.g. BERT, LSTM) Solid knowledge of SQL and Python's ecosystem for data analysis (Jupyter, Pandas, Scikit-Learn, Matplotlib, etc.) Understanding of model evaluation, data pre-processing techniques (standardisation, normalisation, handling missing data) Solid understanding of statistics; hypothesis testing, probability distributions, sampling techniques Private Health Care More ❯
a focus on areas such as robustness, explainability, or uncertainty estimation. Advanced programming and mathematical skills with Python and an experience with the standard Python data science stack (NumPy, pandas, Scikit-learn etc.). The ability to conduct and oversee complex technical research projects. A passion for leading and developing technical teams; adopting a caring attitude towards the personal and More ❯
analytics and hands-on experience and solid understanding of machine learning and deep learning methodsExtensive experience with machine learning and deep learning toolkits (e.g.: TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas)Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goalsExperience with big data and scalable model training More ❯
lifecycle. Experience with APIs or working with different data sources. Desirable: Experience with Azure technologies . Certification in Power BI/Data Engineering , Azure fundamentals . Familiarity with Python, Pandas, or ML concepts (a plus, but not required ). Worker Type: Employee About Us Cubic creates and delivers technology solutions in transportation that make people's lives easier by simplifying More ❯
and have in-depth knowledge of how they work Python: You have built and deployed production-grade Python applications and you are familiar with data science libraries such as pandas and scikit-learn Tooling & Environment : DevOps: You have experience working with DevOps tooling, such as gitops, Kubernetes, CI/CD tools (we use buildkite) and Docker Cloud: You have worked More ❯
underwriting, fraud, and customer conversion. It’s a hands-on role, working with structured and unstructured data in a fast-paced, collaborative team. What You’ll Bring Strong Python (pandas, sklearn) and advanced SQL Experience in behavioural or credit modelling Solid understanding of ML algorithms, drift, and monitoring Ability to communicate clearly across technical and non-technical teams Strong data More ❯
City of London, London, United Kingdom Hybrid / WFH Options
Datatech Analytics
underwriting, fraud, and customer conversion. It’s a hands-on role, working with structured and unstructured data in a fast-paced, collaborative team. What You’ll Bring Strong Python (pandas, sklearn) and advanced SQL Experience in behavioural or credit modelling Solid understanding of ML algorithms, drift, and monitoring Ability to communicate clearly across technical and non-technical teams Strong data More ❯
london, south east england, united kingdom Hybrid / WFH Options
Datatech Analytics
underwriting, fraud, and customer conversion. It’s a hands-on role, working with structured and unstructured data in a fast-paced, collaborative team. What You’ll Bring Strong Python (pandas, sklearn) and advanced SQL Experience in behavioural or credit modelling Solid understanding of ML algorithms, drift, and monitoring Ability to communicate clearly across technical and non-technical teams Strong data More ❯
london (city of london), south east england, united kingdom Hybrid / WFH Options
Datatech Analytics
underwriting, fraud, and customer conversion. It’s a hands-on role, working with structured and unstructured data in a fast-paced, collaborative team. What You’ll Bring Strong Python (pandas, sklearn) and advanced SQL Experience in behavioural or credit modelling Solid understanding of ML algorithms, drift, and monitoring Ability to communicate clearly across technical and non-technical teams Strong data More ❯
groups will be slit accordingly) Data Skills programmes: No-code Programme - Data visualisation, data cleaning, data analytics, statistics, Power BI Extended Programme - All of the above, plus basic Python (Pandas), SQL, and practical machine learning Course Format: Full-time: 10-12 weeks, one weekday (09:00 - 17:30) Evenings: 16 weeks, two evenings per week (18:00-21:00) Contract More ❯
years’ experience in a Data Science, AI, or ML-related role Experience with forecasting, propensity and segmentation Strong Python skills and experience with libraries like scikit-learn, pandas, and Prophet Hands-on experience developing and deploying ML models in production A track record of working across the full ML lifecycle in a fast-paced environment Excellent communication and storytelling skills More ❯
years’ experience in a Data Science, AI, or ML-related role Experience with forecasting, propensity and segmentation Strong Python skills and experience with libraries like scikit-learn, pandas, and Prophet Hands-on experience developing and deploying ML models in production A track record of working across the full ML lifecycle in a fast-paced environment Excellent communication and storytelling skills More ❯
years’ experience in a Data Science, AI, or ML-related role Experience with forecasting, propensity and segmentation Strong Python skills and experience with libraries like scikit-learn, pandas, and Prophet Hands-on experience developing and deploying ML models in production A track record of working across the full ML lifecycle in a fast-paced environment Excellent communication and storytelling skills More ❯
london (city of london), south east england, united kingdom
Harnham
years’ experience in a Data Science, AI, or ML-related role Experience with forecasting, propensity and segmentation Strong Python skills and experience with libraries like scikit-learn, pandas, and Prophet Hands-on experience developing and deploying ML models in production A track record of working across the full ML lifecycle in a fast-paced environment Excellent communication and storytelling skills More ❯
City of London, London, United Kingdom Hybrid / WFH Options
Anson Mccade
business leaders make informed decisions through robust data engineering and analysis. Key Responsibilities Perform complex data manipulation, analysis, and modelling to support senior stakeholders. Build scalable solutions using Python (Pandas, NumPy) and SQL for large, complex datasets. Contribute to data pipelines and workflows on Google Cloud Platform (BigQuery) . Translate business requirements into effective data engineering solutions. Work closely with … services experts in the asset management, investments, and reinsurance domains. Must Have Domain knowledge: Strong background in asset management, investments, or reinsurance. Python expertise: Proven experience with data libraries (Pandas, NumPy). SQL: Advanced data manipulation and querying skills. Cloud experience: GCP/BigQuery (or similar cloud platforms). Education: Degree in Investments, Accounting, Actuarial Science, or related discipline from More ❯
tools, and data pipelines to assist portfolio managers in making informed investment decisions. The ideal candidate will be proficient in Python and have experience working with data structures like Pandas to build scalable and efficient solutions in a fast-paced, dynamic environment. Responsibilities Collaborate closely with equity portfolio managers to understand their needs and develop software solutions to enhance portfolio … to analyze large datasets and derive actionable insights for equity portfolios. Build and maintain data pipelines, ensuring data accuracy, reliability, and scalability. Use Python (and related libraries such as Pandas, NumPy, etc.) to develop and automate tasks, backtest strategies, and optimize performance. Work with portfolio managers to create tools for portfolio construction, risk analysis, and scenario modeling. Ensure seamless integration … Qualifications Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, Physics, Finance, or a related field. Strong proficiency in Python, with a deep understanding of libraries like Pandas, NumPy, and others for data manipulation and analysis. Solid understanding of financial markets, particularly equities, and portfolio management concepts. Knowledge of databases (SQL, NoSQL) and experience in working with large More ❯
tools, and data pipelines to assist portfolio managers in making informed investment decisions. The ideal candidate will be proficient in Python and have experience working with data structures like Pandas to build scalable and efficient solutions in a fast-paced, dynamic environment. Responsibilities Collaborate closely with equity portfolio managers to understand their needs and develop software solutions to enhance portfolio … to analyze large datasets and derive actionable insights for equity portfolios. Build and maintain data pipelines, ensuring data accuracy, reliability, and scalability. Use Python (and related libraries such as Pandas, NumPy, etc.) to develop and automate tasks, backtest strategies, and optimize performance. Work with portfolio managers to create tools for portfolio construction, risk analysis, and scenario modeling. Ensure seamless integration … Qualifications Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, Physics, Finance, or a related field. Strong proficiency in Python, with a deep understanding of libraries like Pandas, NumPy, and others for data manipulation and analysis. Solid understanding of financial markets, particularly equities, and portfolio management concepts. Knowledge of databases (SQL, NoSQL) and experience in working with large More ❯
working in the gaming industry is a plus. Technical Requirements Advanced/Expert - Excel Intermediate/Advanced - Power BI (or similar BI tool) Advanced - SQL Intermediate/Advanced - Python(pandas, sklearn) Nice to have - IBM Planning Analytics Why Product Madness ? As part of the Aristocrat family, we share their mission of bringing joy to life through the power of play … working in the gaming industry is a plus. Technical Requirements Advanced/Expert - Excel Intermediate/Advanced - Power BI (or similar BI tool) Advanced - SQL Intermediate/Advanced - Python(pandas, sklearn) Nice to have - IBM Planning Analytics Why Product Madness ? As part of the Aristocrat family, we share their mission of bringing joy to life through the power of play More ❯
Lyst is a global fashion shopping platform founded in London in 2010 and catering to over 160M shoppers per year. We offer our customers the largest assortment of premium & luxury fashion products in one place, curating pieces from 27,000 More ❯
About the roleWe are excited to be hiring a new Data Scientist into our team! Lendable is the market leader in real rate risk-based pricing, offering consumers transparency and product assurance at the point of application. Data Science sits More ❯