18 of 18 NumPy Jobs in Central 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 ...

with clear opportunities to contribute to systems that will define the firm’s next decade. What We’re Looking For Strong Python skills (pandas, NumPy, SQLAlchemy, etc.) Experience working in business-facing engineering roles Background in automating workflows, building internal tools, or integrating data-driven systems Knowledge of mortgages, fixed ...

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 ...

Word2Vec, TF-IDF, Word Embeddings Transformers: BERT, ELMo OpenAI Models: GPT-3.5 Turbo, GPT-4o, GPT-3o Reasoning, text-embedding-ada-002 Libraries & Tools numpy, pandas, scipy, scikit-learn, tensorflow, keras, nltk, matplotlib, seaborn, plotly Programming Languages Python, R, C++, C#, Java, Node.js, HTML, SQL Agentic AI OpenAI Agents ...

engineering, ideally within quantitative finance. Advanced degree in a quantitative discipline (Mathematics, Physics, Computer Science, Engineering). Strong Python programming skills (experience with Pandas, NumPy; familiarity with Polars a plus). Proven ability to work with large-scale alternative and traditional financial datasets. Interest in financial markets and applying data ...

Ensure data quality, governance, and lineage tracking throughout the project. Required Skills ETL/ELT pipeline design and data validation frameworks. Advanced Python (pandas, numpy, boto3) and SQL (complex queries, optimisation). Experience with AWS Glue , Step Functions , and event-driven architectures . Knowledge of vector databases , embeddings, and semantic ...

across domains such as NLP, computer vision, audio, graphs, time-series or tabular data Strong Python skills and experience with common libraries (e.g. pandas, NumPy, scikit-learn, PyTorch, Transformers, statsmodels, PyMC) Understanding of software engineering and ML best practices, including version control, packaging and model deployment Experience training and deploying ...

statistical inference is highly valued. Python expertise: Skilled 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 ...

audiences Mentor junior data scientists and help shape AI best practice Requirements Strong experience in AI, machine learning and statistics Python expertise (e.g. pandas, NumPy, scikit-learn, PyTorch, transformers) Experience deploying models and working with cloud platforms (AWS preferred) Ability to communicate complex technical concepts clearly Desirable AWS services (SageMaker ...

deliver commercial impact. A strong academic background (Bachelor’s degree 2:1 or above in a quantitative subject). Strong Python skills (Pandas, NumPy, Scikit-learn or similar). A collaborative mindset with excellent communication skills. Experience working in cross-functional teams delivering production-ready solutions. If this role looks ...

with SAP data structures is beneficial Integration with PIM (Product Information Management) systems Design and consumption of REST APIs Programming & Querying Python (advanced): pandas, numpy, boto3, and data processing best practices SQL (advanced): complex queries, performance tuning, and query optimization Data Quality & Governance Data profiling and ongoing quality assessment Schema ...

data. Several years' experience as a data scientist in industry or related environments. Proficiency in Python and common ML/data libraries (e.g., pandas, numpy, scikit-learn, PyTorch, transformers). Understanding of software and ML engineering best practices (git, package development, model deployment). Experience with cloud platforms, particularly ...

applied across multiple domains (NLP, vision, audio, time series, tabular data). Proficient in Python and relevant ML/data science libraries (e.g., pandas, numpy, scikit-learn, PyTorch, transformers). Experience with cloud-based model deployment (AWS) and ML engineering best practices. Excellent communication, problem-solving, and project delivery skills. ...

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. ...

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. ...

About you Master’s or PhD in AI, Machine Learning, Data Science, or Computer Science (Russell Group or similar). Strong Python skills (Pandas, NumPy). Experience or exposure to NLP, transformers, and LLMs. Familiarity with ML tools like Weights & Biases or MLflow is a plus. Curious, proactive, and confident ...

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 ...

classes, and object-oriented programming, List comprehensions, generators, Error handling, iii. Working with virtual environments and package management (pip, venv) Data Manipulation & Analysis (Pandas & NumPy) i. Key libraries: pandas, numpy, (optional: polars) ii. Key skills: Data cleaning and preprocessing, Handling missing values, grouping, merging, pivoting, aggregations, and SQL Software Engineering ...