12 of 12 Pandas Jobs in Central London

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, AWS Bedrock ...

optimization. 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 ...

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 CI for maintaining ...

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 ...

with 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 ...

internships/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 ...

optimizations; Machine Learning deployments on AWS, Azure or GCP Extensive hands-on data science experience, leveraging machine learning and data science tools (i.e., pandas, scikit-learn, PyTorch, etc.) Experience with DevOps tools: Kubernetes, Docker, Terraform, CI/CD Pipelines, GitHub/GitLab, GitOps, GitHub Actions, Jira, Jenkins, CircleCI, Datadog, Slack. ...

Background 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 ...

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: Active ...

Data Engineering, SRE, SWE or Data Ops roles in high performance, time sensitive environments. Strong Python proficiency, including exposure to libraries such as Pandas, Arrow, and Spark. Strong grasp of data modelling, normalization and API development for large scale analytical or trading systems. Experience with lakehouse architectures (Databricks ideally ...

both technical and non-technical stakeholders, including coaches, scouts, analysts, and traders. Skills & Attributes Strong background in Python, with experience in data manipulation (Pandas/Polars) and statistical modelling. Industry experience in a data science role focussing on sports analytics. Knowledge of advanced football metrics (possession value models highly desirable ...

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 of key product modules … 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 building analytics/ ...