14 of 14 Remote/Hybrid NumPy Jobs in London

/stress-testing, simulation analysis, rare event modeling, and stochastic modeling preferred but not required. Substantial experience with Python, R, and relevant libraries (e.g., numpy, pandas, scikit, pytorch, tidyverse, caret, ggplot, etc.). Proven experience developing, refining, and monitoring NLP models. Familiarity with database management tools and techniques (e.g. ...

with hands-on experience productionising models and building scalable ML systems. Machine Learning Engineer, key skills: Strong experience in Python (e.g. pandas, scikit-learn, NumPy, TensorFlow/PyTorch) Proven experience in model productionisation and deployment in real-world environments Hands-on experience with MLOps, including CI/ ...

with hands-on experience productionising models and building scalable ML systems. Machine Learning Engineer, key skills: Strong experience in Python (e.g. pandas, scikit-learn, NumPy, TensorFlow/PyTorch) Proven experience in model productionisation and deployment in real-world environments Hands-on experience with MLOps, including CI/ ...

stress-testing, simulation analysis, rare event modeling, and stochastic modeling preferred but not required. Substantial experience with Python , especially data-science-relevant libraries (e.g., numpy, pandas, scikit-learn, etc.). Familiarity with database management tools and techniques (e.g., SQL, S3, API protocols) preferred but not required. Understanding of model evaluation ...

architecture, mentor engineers and scientists, lead applied research initiatives What You'll Bring Technical Expertise: Strong Python skills with the ML stack: NumPy, pandas, scikit-learn Hands-on experience with at least one deep learning framework (PyTorch, TensorFlow, JAX) Solid grounding in core ML—supervised, unsupervised, evaluation, regularisation, statistics Production ...

least 2 years’ experience working as a data engineer (ideally consulting/financial services) – salary and level will reflect experience. Proficiency in Python (pandas, numpy) Professional experience with Azure cloud services (AWS/GCP acceptable with deeper experience) Strong experience deploying clean, maintainable, production-level code. Basic understanding ...

semi-structured, or unstructured data, especially large-scale text or content datasets. Familiarity with common data science and machine learning tools such as Pandas, NumPy, SciPy, Scikit-learn, PyTorch, TensorFlow, or Matplotlib. The ability to translate complex and ambiguous requirements into practical, measurable, data-driven solutions, with strong analytical thinking ...

engineering and product teams to transform raw data into robust, auditable, and commercially valuable solutions. Skills & Experience Technical Expertise Strong proficiency in Python (Pandas, NumPy, Scikit-learn) and SQL . Hands-on experience with Snowflake or similar cloud-based data warehouse platforms. Experience using Git and reproducible development practices. Strong ...

Storage (ADLS). Solid understanding of Scrum practices and a strong Agile mindset. Advanced proficiency in Python and its key data and ML libraries (NumPy, PySpark, Scikit learn, TensorFlow/PyTorch) Working knowledge of generative AI models (e.g., ChatGPT, Claude), Databricks GenAI tooling (including embedding models), and modern data structures ...

succeed: Extensive hands-on Python Development experience building REST APIs with FastAPI or similar. Strong quantitative background - must have. Strong experience with Pandas, NumPy, and/or SciPy. Good experience with time series or market data models. Experience with Docker, Kubernetes, and Cloud. What you'll get in return: Initial ...

bachelor’s degree level or equivalent qualification/relevant work experience Excellent programming skills, predominantly across the Python/Anaconda suite (Scikit-learn, Pandas, Numpy) Understanding financial markets, risk (for example, Know Your Client (KYC), anomaly detection/Machine Learning, project management Excellent interpersonal skills with the ability to collaborate ...

professional industry setting (excluding post‐doc positions), with exposure to: building machine learning models and pipelines in Python, using common libraries and frameworks (e.g., NumPy, SciPy, Pandas, PyTorch, JAX), especially including deep learning applications; developing models for bespoke problem settings that involve high‐dimensional data (spatiotemporal, geometric, physical); iterating ...

been instrumental in: building machine learning models and pipelines in Python, using common libraries and frameworks (PyTorch/CUDA, ideally with exposure to JAX, NumPy/SciPy), especially including deep learning applications; developing models for bespoke problem settings that involve high‐dimensional data (spatiotemporal, geometric, physical); iterating on network architectures ...

Experience in machine learning Exposure to machine learning models and corresponding statistics like K‐means, Bayesian, Clustering Strong technical skills with Python along with NumPy, Pandas, Scikit‐Learn Machine learning experience -> predictive and prescriptive modelling Data wrangling and data cleansing experience Strong analytical skills Any experience with Node.JS would … IOS. Experience in Java and Python. Exposure to MVC frameworks such as spring, hibernate, & other java related frameworks. Exposure to packages in Python, including numpy, pandas, matplotlib, etc. Familiar with relational & non‐relational databases such as SQL Server, MySQL, Mongo. Experience interacting with REST APIs. Developed web services and used ...