12 of 12 Remote 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 ❯

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 ❯

learning, particularly in recommendation systems and deep learning architectures Strong understanding of two-tower neural networks, embedding techniques, and ranking models Proficiency in Python and ML libraries (e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku Experience with ML Ops, including deployment, monitoring, and retraining pipelines Ability to work cross 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 ❯

domain knowledge: understanding of financial concepts, metrics, or fintech/finance experience Experience building data pipelines, ETL processes, or handling large-scale data Familiarity with modern data processing libraries (NumPy, Polars, DuckDB) What we're looking for Beyond the technical requirements, we value engineers who: Are self-motivated and eager to learn and expand their skills Possess an analytical mindset 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 ❯

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 ❯

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 ❯

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 ❯

Scientist, your background will include: 3+ years industry experience in a Data Science role and a strong academic background Python Data Science Stack: Advanced proficiency in Python , including pandas , NumPy , scikit-learn , and Jupyter Notebooks . Statistical & ML Modelling: Strong foundation in statistical analysis and proven experience applying a range of machine learning techniques to solve business problems (e.g., regression More ❯

ideas with the wider team, learn from and contribute to the body of knowledge. Key Skills Experience using Python and SQL. Strong proficiency with data manipulation including packages like NumPy, Pandas. Knowledge of machine learning techniques and their respective pros and cons. Confident communicator and contributes effectively within a team environment. Self driven and willing to lead on projects/ More ❯