11 of 11 NumPy Jobs in the City of London

trading technology. 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 ...

Confluent 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 ...

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 ...

understanding the limitations of the language) and in building data pipelines and ML models using modern libraries across multiple domains: Data science stack: NumPy, pandas/polars, scikit-learn, XGBoost, LightGBM Deep learning: PyTorch, JAX Statistical programming: NumPyro, PyMC Data skills: Proficient in SQL, with the ability to write efficient ...

generation toolsets for API development. Some experience with Python, modern development techniques, and design patterns. Experience in data science tools and ML tools (e.g., NumPy, pandas, scikit-learn, PyTorch) and open-source contributions (especially Python-based) would be a bonus. Familiarity with CUDA, GPU-based computations, end-to-end neural ...

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 ...

experience in data analysis or data science (graduate roles, internships, placements, or academic projects welcome) 🐍 Strong Python experience for data analysis and modelling (pandas, NumPy, scikit-learn or similar) 🗄 Solid experience working with SQL and structured datasets ☁️ Hands-on experience using AWS (e.g. S3, RDS, Athena, Glue, or similar ...

science in a commercial setting. Proven track record in customer or marketing analytics - understanding acquisition, engagement, churn, and lifetime value. Proficiency in Python (Pandas, NumPy, Scikit-learn, Statsmodels) for data wrangling, analysis, and modelling. Ability to communicate complex findings in a clear, business-relevant way. Experience working collaboratively in agile ...

data science projects from conception to delivery. Experience with customer focused Data Science techniques - especially around personalisation and recommenders. Proficiency in Python (Pandas, NumPy, Scikit-learn, Statsmodels, Matplotlib) for analysis, modelling, and visualisation. Experience with customer, product, or financial analytics - understanding drivers of engagement, retention, and value. Track record ...

including data governance and fairness in highly regulated financial settings. Key Technologies & Tools Core ML: scikit-learn, PyTorch, TensorFlow, XGBoost, LightGBM Data Manipulation: Pandas, NumPy, LangGraph MLOps & Orchestration: MLflow, Apache Airflow Databases: Neo4j, MongoDB API Development: FastAPI Big Data (Beneficial): Apache Hadoop, Apache Spark (PySpark) What We Need From ...

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 ...