1 to 25 of 36 NumPy Jobs in London

Science, Engineering, AI, or related field. 7+ years of professional software development experience, with at least 3 years in AI/ML. Strong proficiency in Python , including libraries like NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch . Solid understanding of ML algorithms , NLP , deep learning , and statistical methods. Experience with Docker, Kubernetes , and cloud platforms like AWS/Azure/GCP More ❯

as subject-matter expert for pricing models and valuation logic, supporting risk and trading teams globally. Skills and Experience Expert-level Python developer with strong experience in numerical computing (NumPy, SciPy, Pandas). Deep understanding of derivatives pricing theory, volatility modelling, and stochastic calculus. Experience with calibration, curve bootstrapping, and risk measures (Greeks, sensitivities, VaR). Background in pricing and More ❯

between technology initiatives and business objectives. Required Qualifications: 6+ years of experience in full stack software development. Proficiency in sever side Python programming. Proficiency in data analysis using Pandas, Numpy, SciPy etc. Experience with object oriented design, distributed systems architecture, performance tuning. Experience with designing and programming relational database such as MySQL, RedShift, Oracle SQL Server, or Postgres. Experience with More ❯

managing cloud services like Google Cloud and AWS. Bonus points Startup experience Experience with Python web services (e.g. FastAPI, Django). Data engineering experience using PyData stack technologies (e.g. NumPy, Pandas, etc.) Experience building machine learning systems with LLMs, RAGs utilising embeddings. Technology Frontend: Typescript, , Vercel Backend: Go, Postgres, , Google Cloud Services: GitHub, Sentry, Stytch, OpenAI Perks & Benefits (for UK More ❯

up? Having added nearly 100 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 notebooks Exposure to machine learning More ❯

up Having added nearly 100 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 notebooks Exposure to machine learning More ❯

deep learning, reinforcement learning, generative models). Support continuous model improvement and scalable MLOps deployment pipelines. TECH STACK/REQUIREMENTS Core Skills: Python, TensorFlow/PyTorch, scikit-learn, OpenCV, NumPy, Pandas Experience With: Model training, tuning, and deployment in production environments Preferred: Sports data analytics, time-series forecasting, or computer vision experience Infrastructure: AWS/GCP/Azure, Docker, Kubernetes More ❯

libraries (Matplotlib, Seaborn.) SQL for 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 and optimisation. Calculus for optimising More ❯

and machine learning techniques (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, monitoring, and retraining pipelines. ? Ability to More ❯

Have 5+ years professional Python development experience. Extremely effective in writing clean, modern Python code. Experience building and documenting high-quality APIs for developers. Deep Python ecosystem expertise: Pandas, Numpy, Bokeh, PyArrow, matplotlib, IPyWidgets, Jupyter, uv, etc. Proven experience building large data pipelines/ETL workflows. Comfortable working in Jupyter notebooks. An understanding of crypto or TradFi markets and trading More ❯

maintain in-house applications for the Derivatives trading desk using Python Implement automated testing with PyTest and ensure code quality through peer reviews Process, analyse, and manipulate data using NumPy and Pandas Manage CI/CD pipelines to ensure stable production environments Utilise Git-based workflows for collaborative development Work closely with team members and stakeholders to deliver user-focused More ❯

experience delivering data migration or integration projects , ideally with ERP/CRM systems such as Microsoft Dynamics . Strong technical skills in Python , including libraries such as Pandas and NumPy . Hands-on experience with ETL design, data warehousing, and relational databases (SQL). Advanced proficiency in SQL and data modelling techniques. Knowledge of cloud data platforms (Azure preferred, AWS More ❯

t always work with our data, so you will need to understand how to develop your own models Strong programming skills and experience working with Python, scikit-learn, SciPy, NumPy, Pandas and Jupyter Previous experience in finance is not required, although an interest in finance and the motivation to rapidly learn more is a prerequisite for working here. Why should More ❯

leverage AI tooling to get bootstrapped quickly is a must. Core AI & Machine Learning Python Vertex AI/Hugging Face LangChain/BAML — LLM frameworks Langfuse, LangSmith — Observability Pandas, NumPy, scikit-learn, PyTorch — Data & ML stack Data & Infrastructure BigQuery — Cloud data warehouse PostgreSQL — Application data Pulumi — Infrastructure as Code (TypeScript) Google Cloud Platform (GCP) — Cloud provider GitHub Actions — CI/ More ❯

complex datasets. Desirable Experience & Skills Practical knowledge of data engineering practices (designing and building robust data pipelines) Knowledge of python and core libraries applicable to data science (e.g., pandas, numpy, statsmodel More ❯

secure, deployable AI solutions Key Skills & 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 methods (e.g. ML, NLP More ❯

to internal capability-building by sharing knowledge, tools, and best practices within the wider team What They’re Looking For Strong Python skills and comfort using core libraries (e.g. NumPy, Pandas), plus familiarity with deep learning tooling like PyTorch Expertise in a wide range of ML methods, including supervised and unsupervised learning, time series, or NLP and LLM/GenAI More ❯

initiatives, including price, volume, and mix analysis and margin optimisation . Tech Environment Core Skills: SQL (essential), Power BI (advantageous) Platform: Microsoft Fabric (mid-implementation) Languages: Python (pandas/numpy - desirable, not essential) Other: Salesforce & Google Analytics exposure beneficial About You Proven experience as an Insight Analyst , ideally in wholesale, distribution, or another product-heavy industry. Strong knowledge of pricing More ❯

and reaction kinetics. Interest in simulation, modeling workflows, and their application in real-world pharma/biotech contexts. Basic to intermediate Python programming skills, especially with scientific libraries (e.g., NumPy, SciPy, pandas). Nice to Have Experience with Pyomo or CasADi. Familiarity with bioprocesses or pharma case studies. Curiosity about AI, workflow automation, or cloud-based platforms. Soft Skills Proactive More ❯

fit if you: Have over 3+ years of professional experience in data science or applied analytics. Are highly skilled in Python and Jupyter notebooks. Have experience using libraries including numpy, pandas, scipy, sympy, scikit-learn, torch, tensorflow. Have a bachelor's degree in data science, statistics, computer science, or related field in the U.S., Canada, New Zealand, UK or Australia. More ❯

or personalization/recommendation. Familiarity with state-of-the-art practice in these domains Proficient in Python, and experience with machine learning and deep learning toolkits (e.g., TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas) Scientific thinking, ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals Solid written More ❯

ready using methodologies. Python 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. AI & Machine Learning Frameworks - Deep expertise More ❯

ready using methodologies. Python 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. AI & Machine Learning Frameworks - Deep expertise More ❯

related technical discipline. Good knowledge of machine learning and computer vision algorithms. Familiarity with real-time imaging pipelines. Experience with scientific software packages such as PyTorch, OpenCV, Pandas, SciPy, NumPy, SciKit's, etc. Experience in standard software engineering practices including version control systems and software testing methodologies. Excellent oral and written communication skills. Analytical thinker, attentive to details, creative and More ❯

application (e.g., regression, classification, clustering, time-series forecasting, survival analysis). Solid object-oriented programming skills in Python and hands-on expertise with the core data science stack (Pandas, Numpy, Scikit-learn, XGBoost/LightGBM). A proven ability to break down vague, complex problems into concrete, solvable steps. Excellent communication and data storytelling skills. You can build strong relationships More ❯