10 of 10 Permanent NumPy Jobs in Central London

programming languages such as Python, R, or SQL, and experience with various data science and machine learning libraries. Experience with libraries/frameworks like NumPy, Pandas, SciPy, Scikit‐learn, TensorFlow, PyTorch, Transformers, Langchain, Streamlit, or Gradio, among others. Experience with cloud‐based tools for production use (e.g., AWS SageMaker ...

parallelised applications, including memory management. Experience with widely used tools in data science and machine learning. Developers should be somewhat familiar with libraries like NumPy, pandas, scikit-learn, and PyTorch. Proficiency in testing approaches and frameworks like pytest as well as automation tools like Github Actions or Travis ...

Experience with distributed systems, parallel computing, and high-performance processing of large datasets. Strong experience in data pipelines, working with tools such as Pandas, NumPy, and SQL/NoSQL databases. Proven experience working in fast-paced environments, ideally within trading, financial services, or high-frequency environments. Proficiency in developing RESTful ...

applying causal inference techniques (e.g., diff-in-diff, IV, matching) where randomisation is impractical Fluency in Python and core data/ML libraries (pandas, NumPy, scikit-learn, PyTorch or TensorFlow), combined with solid software engineering practices (clean code, testing, version control, code review) Proficient with large-scale data : strong ...

investors and engineers to forecast key company KPIs, design real-time dashboards, and develop best-in-class data infrastructure. Key Requirements Strong Python (pandas, NumPy, scikit-learn; PyTorch/TensorFlow a plus) and SQL skills Experience applying advanced analytics or ML to real-world data (finance, fintech, or forecasting contexts ...

3+ years of industry experience as a Data Scientist , plus a strong academic foundation Python Data Science Stack : Advanced proficiency in Python , including Pandas, NumPy and scikit-learn. Statistical & Machine Learning Modelling : Experience with a variety of ML techniques ( regression, classification, clustering, time-series forecasting ) Experience with deep learning frameworks ...

/placements welcome in addition) Strong SQL skills and confidence working with relational data and large datasets Strong Python for analysis/automation (pandas, NumPy; good coding hygiene) Essential: Dashboarding experience in Power BI, Tableau, or Looker (building and maintaining stakeholder-facing dashboards) Solid understanding of analytics fundamentals: data cleaning ...

commercial experience in Machine Learning Strong experience in Computer Vision (e.g. object detection, image classification, segmentation) Experience building, training and optimising ML models Python (NumPy, Pandas, scikit-learn) and frameworks such as TensorFlow or PyTorch Experience deploying models into production environments (cloud platforms, Docker, CI/CD pipelines) Clearance requirements ...

challenges while keeping performance and scalability in mind. Apply software engineering best practices—SOLID principles, design patterns, unit & integration testing. Work with modern tech: NumPy, SciPy, Pandas, SQL, Docker, Kubernetes, cloud platforms, CI/CD. Collaborate with an international team across the UK, Netherlands, and US. Take ownership … product modules and influence software architecture. 🏆 What we’re looking for: 5+ years Python experience, especially with scientific libraries (NumPy, SciPy, Pandas). Relevant degree (Maths, Computer Science, or related quantitative field). Strong maths/statistics/analytics background, with experience translating theory into production-ready Python code. Experience ...

StatArb platform. Live since 2021, trading 24/6 globally. Unified graph-based framework (DAG) across research, production, analytics, risk, and P&L. Deep Numpy/Numba work, processing vast historical datasets and real-time tick data. You'll contribute to shared tooling that researchers actually rely on. … lines. What you'll need: 5+ years as a Quant Dev in a systematic hedge fund (StatArb/equities experience ideal) Deep Python expertise (Numpy/Numba) Strong grasp of statistical methods, numerical optimisation, and equity market microstructure Experience with Unix internals and graph-based data processing frameworks What ...