8 of 8 SciPy Jobs in London

Advanced degree (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 ...

Engineer Research-led or data-heavy environments where engineering quality and problem-solving matter Core Requirements Strong Python experience in production environments (pandas, numpy, scipy or similar) Experience building research, analytics or decision-support tooling Solid software engineering fundamentals: testing, version control, deployment Comfortable working with ambiguity and taking ownership ...

Delta Lake Airflow/Databricks Workflows Cloud Platforms Azure, AWS, or GCP (experience with at least one) Data Science & Optimisation Python ecosystem (Pandas, NumPy, SciPy, Statsmodels) Scikit‐learn, XGBoost, LightGBM, CatBoost Time‐series forecasting (Prophet, SARIMAX, ML‐based approaches) Optimisation frameworks (OR‐Tools, Pyomo) Agentic AI & LLMs (Nice to Have ...

comfortable with ambiguity and will want to dive deep and fix problems at scale. The environment looks a bit like this 👇 👉 Python (pandas, numpy, scipy, PySpark) 👉 SQL 👉 AWS or GCP (BigQuery/RedShift/Snowflake) 👉 Spark/Databricks 👉 Airflow/Dagster ...

exposure, generation patterns, demand profiles, and commercial optimisation. Required Skills and Experience Technical Skills Proficiency in Python and associated data science libraries (NumPy, Pandas, SciPy, scikit‐learn, PyTorch/TensorFlow). Strong experience with time‐series modelling (ARIMA, Prophet, LSTMs or similar). Understanding of optimisation methods (linear, mixed‐integer ...

over time. Required Skills and Qualifications Technical Expertise (The Core) Programming: Expert proficiency in Python and its core data science libraries: Pandas, NumPy, and SciPy . Machine Learning: Deep, practical experience with popular ML frameworks and libraries: scikit-learn, TensorFlow, or PyTorch . Statistics & Math: Strong foundation in statistical modeling ...

with recommender systems, personalisation, or deep learning is desirable but not essential. Solid Python skills and experience with ML libraries such as pandas, numpy, scipy, scikit-learn, TensorFlow or PyTorch. Experience working across cloud environments (GCP, AWS, or Azure) and analytics platforms such as Dataiku. Good understanding of MLOps practices ...

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 of key 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 building ...