1 to 25 of 45 Pandas Jobs in London

shared team practices Mentor peers and help grow a high-trust, high-impact engineering culture Tech Stack Python 3.x with FastAPI, Pydantic, SQLAlchemy, Pandas, and NumPy Relational databases: MySQL and PostgreSQL GCP experience is a plus, but not required Modern Middleware is a plus – e.g. Pub/Sub, Memcache Docker ...

Master's or PhD) in Mathematics, Physics, Financial Engineering, or a closely related quantitative discipline. Advanced Python engineering capability (inc. NumPy/SciPy/Pandas). Strong understanding of derivatives pricing theory. Background working with commodity or equity options, including structured derivatives. Solid understanding of Greeks, risk measures, and valuation ...

Python developer, ideally within high-performance, data-heavy environments. Strong grounding in computer science fundamentals — algorithms, data structures, and system design. Experience with NumPy, Pandas, PySpark, or similar data frameworks. Exposure to financial data, trading systems, or quantitative research is highly advantageous (though not required). Passion for clean, performant ...

actionable insights for trading and risk management. Document system architecture, data flows, and technical processes for transparency and reproducibility. Requirements Strong proficiency in Python (pandas, NumPy, PySpark) and ETL development. Hands-on experience with AWS services (S3, Glue, Lambda) and Databricks. Solid understanding of financial market data, particularly time-series. ...

Data Engineer: Extensive hands-on experience with AWS data services Strong programming skills in Python (including libraries such as PySpark or Pandas) Solid understanding of data modelling, warehousing and architecture design within cloud environments Experience building and managing ETL/ELT workflows and data pipelines at scale Proficiency with ...

researchers to design pipelines for modeling and back-testing. Document and maintain the firm’s core data architecture. Requirements: 5+ years of Python development (Pandas, SQL, Linux environment). Hands-on experience building data solutions for trading, research, or risk. Deep technical curiosity and strong problem-solving skills. Strong knowledge ...

data extraction and manipulation. Experience working with large datasets. Technical Skills Proficiency in cloud computing and python programming. Familiarity with Python libraries like Pandas, NumPy, scikit-learn. Experience with cloud services for mode training and deployment. Machine Learning Fundamentals Statistical concepts for robust data analysis. Linear algebra principles for modelling ...

full-time roles in 2026 Experience programming in Python and/or C++ Experience with statistical analysis, numerical programming, or machine learning in Python, Pandas/Numpy, R, and/or MATLAB A passion for applying quantitative models and technology toward solving real-world problems Brilliant analytical and problem-solving ...

supervised and unsupervised learning, natural language processing, Bayesian statistics, time-series forecasting, collaborative filtering etc) ? Proficiency in Python with familiarity to ML libraries e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) ? Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku, Databricks. ? Experience with ML Ops, including model deployment ...

familiarity with core ML concepts (classification, time-series, statistical modeling) and their real-world tradeoffs. Fluency in Python and commonly used ML libraries (e.g. pandas, scikit-learn; experience with PyTorch or TensorFlow is a plus). Experience with model lifecycle management (MLOps), including monitoring, retraining, and model versioning. Ability ...

cloud-native model training and deployment, model serving, and effective data lifecycle management. Expert proficiency in Python, SQL, and core ML libraries (e.g., Pandas, NumPy, Scikit-Learn, XGBoost). Strong experience working with cloud-based ML platforms (AWS preferred, e.g., SageMaker). Familiarity with model management and deployment tooling such ...

London-based Financial Services Clients. You will need: Extensive hands-on development experience with Python within Financial Services Strong background working with Pandas & NumPy Good experience with Django and Javascript Strong experience working within a risk environment Proficiency with Python libraries such as click apply for full job details ...

people to the business this year, they're looking for Quantitative Developers with proficiency in Python, and experience with the Python data libraries (Pandas, NumPy) (preferably) from the Trading world. They also are on the look out for candidates who: Have deep familiarity with Python data ecosystem Understanding of Jupyter ...

Experience Required Senior-level experience in data science or a quantitative field Proficient programming skills (Python preferred); familiarity with core data science libraries (NumPy, Pandas, Scikit-Learn) Experience with deep learning tools (e.g. PyTorch, TensorFlow, or similar) Strong mathematical/statistical background Familiarity with a wide range of data science ...

designing and managing workflows for collecting, cleaning, and storing large volumes of financial data (e.g., price, volume, fundamentals, alternative data), often using tools like Pandas, NumPy, and Dask. Collaborate Across Teams for Deployment, working with researchers, traders, and DevOps teams to integrate Python models into production environments (e.g., through APIs ...

years of professional Python development experience. Strong ability to write clean, modern Python code. Experience building and documenting APIs. Deep knowledge of Python ecosystem (Pandas, Numpy, Bokeh, PyArrow, Matplotlib, IPyWidgets, Jupyter, etc.). Proven experience with large-scale data pipelines and ETL workflows. Comfortable working in Jupyter notebooks. Understanding ...

environments. Collaborate across engineering, security, and product teams to deliver at pace and scale. The toolkit you’ll use 🌳 Data Science & Engineering: Python (NumPy, Pandas, scikit-learn, PyTorch/TensorFlow), SQL, NoSQL, Spark, big data ecosystems Visualisation & APIs: REST/JSON, Postman, Flask/FastAPI, Power BI/Tableau, D3.js ...

workflows Design and implement data models and flows that are optimally flexible and performant Proficient in data engineering and data science implementations in Python (Pandas) and SQL Visualization implementations/techniques in DashUI/ag-grid/plotly are a plus Your Skills And Experience Extensive data and analytics experience ...

Development - Strong proficiency in Python programming including object-oriented design, asynchronous programming, error handling, and writing clean, maintainable code. Experience with key libraries including Pandas, NumPy for data manipulation, requests and APIs for integrations, asyncio for concurrent processing, and building robust automation scripts with proper logging, testing (pytest), and documentation. ...

learning, delivering actionable insights and business optimisation solutions. Technical Excellence: Deep proficiency in Python, possibly R for prototyping, SQL, and specialist tools such as Pandas, NumPy, Spark, and Dask; hands-on experience with cloud platforms (Azure ML, AWS) and ML Ops for robust model deployment and automation. CI/ ...

adoption of emerging AI tech. What We’re Looking For 5+ years in data engineering, with team or project leadership experience. Advanced Python (Pandas, PyTorch, TensorFlow, Scikit-learn). Strong AWS/GCP , MySQL , and CI/CD experience; Docker/Kubernetes a plus. Excellent communication, organisation, and problem-solving ...

Python coding. It is essential to have good knowledge of Python built in data types/functionality as well as associated tools such as Pandas/Polars, and web frameworks. The ideal candidate will be passionate about the latest AI/Machine Learning/Automation techniques and tools, with some ...

Requirements: Bachelor's or higher in Computer Science, Engineering, Mathematics, Statistics, or a quantitative discipline. 5+ years developing Python-based financial software, with strong Pandas experience. Exposure to financial datasets across multiple asset classes. Experience supporting quantitative research and modelling. Proficiency in Linux environments. Strong foundation in mathematics and statistics. ...

feedback Stay current with modern technologies and help foster a culture of technical curiosity and improvement Tech Stack Python 3.x with FastAPI, Pydantic, SQLAlchemy, Pandas, and NumPy Databases: MySQL, PostgreSQL, Redis Cloud: GCP (Pub/Sub, Cloud Run, GCE, Cloud Logging) Infra: Docker, Kubernetes, GitLab CI/CD Environments: Linux ...

course not limited to) equities, futures, options, and multi asset classes. Alongside the rest of the Financial Engineering team, you'll leverage pandas and related python libraries to produce MerQube branded financial engines as well as indexing strategies for major financial institutions. You'll interface directly with both clients ...