15 of 15 Permanent NumPy Jobs in East London

of hands-on experience as a Python Developer. Strong proficiency in Python 3.x and frameworks such as Flask , FastAPI , or Django . Solid experience with data libraries like Pandas , NumPy , and Dask . Familiarity with data processing frameworks (e.g., PySpark , Apache Beam ). Proficient in both SQL and NoSQL databases (e.g., PostgreSQL , MongoDB ). Understanding of ETL workflows and tools More ❯

a Data Science related role Proven depth in probability & inference (e.g., Bayesian updating, time-series/state-space models, extreme-value theory). Hands-on Python for numerical analysis (numpy, pandas, xarray, SciPy/PyMC/PyTorch, or similar). Experience validating models with historical data and communicating results to non-specialists. Exposure to real-time data engineering (Kafka, Airflow More ❯

AWS, Python Liaise daily with investment professionals to understand requirements and deliver solutions What we’re looking for: Strong Python developer with deep experience using statistical and numerical libraries (NumPy, pandas, SciPy etc.) Proven experience supporting quant or systematic investment strategies Good understanding of infrastructure – ideally AWS and Snowflake – and willingness to own setup and tooling Comfortable working in fast More ❯

Scikit-learn, XGBoost, LightGBM, StatsModels PyCaret, Prophet, or custom implementations for time series A/B testing frameworks (e.g., DoWhy, causalml) Programming & Data Tools : Python: Strong foundation in Pandas, NumPy, matplotlib/seaborn, scikit-learn, TensorFlow, Pytorch etc. SQL: Advanced querying for large-scale datasets. Jupyter, Databricks, or notebooks-based workflows for experimentation. Data Access & Engineering Collaboration : Comfort working with More ❯

data engineering. Ability to work standard European time-zone hours and legal authorisation to work in your country of residence. Strong experience with Python’s data ecosystem (e.g., Pandas, NumPy) and deep expertise in SQL for building robust data extraction, transformation, and analysis pipelines. Hands-on experience with big data processing frameworks such as Apache Spark, Databricks, or Snowflake, with More ❯

Developer – Market Risk than Credit Risk. Building from the beginning – lots of IT Challenges – Python Code Migrating from library, tweaking, methodology. Skills: Quant Developer Python: Blackrock numeric data processing: numpy, scipy text data processing: pyarrow, pandas databases: sqlalchemy, psycopg parallelization: multiprocessing, concurrent.futures More ❯

A recently completed Master’s degree from a Russell Group university in Data Science, Computer Science, Mathematics, Physics, Engineering, or a related discipline Strong programming skills in Python (e.g. NumPy, pandas, scikit-learn, matplotlib); R is also welcome A solid understanding of core machine learning concepts, data wrangling, and model evaluation Proficiency with SQL and experience handling large datasets A More ❯

like to see from you Experience with Python A keen interest in backend development Understanding of distributed systems (RabbitMQ, Celery, Redis, Memcached) Good knowledge of scientific libraries such as Numpy and Pandas Extensive usage of MongoDB, BigQuery, data visualisation and manipulation tools Experience with designing, training, evaluating machine learning models Familiarity with the main AI frameworks (Pytorch, Tensorflow, scikit-learn More ❯

used for portfolio monitoring and strategy evaluation Candidate Profile: Strong academic background in a quantitative discipline (e.g. maths, finance, engineering, computer science) Hands-on experience with Python (especially Pandas, NumPy) and SQL A solid understanding of, or interest in, financial markets and investment strategies Exposure to performance or risk analysis through internships, projects or coursework is a plus Detail-oriented More ❯

again, and again. Proven track record delivering impactful ML/AI solutions in production. Deep expertise in Python and modern AI/ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn, NumPy, Pandas). Hands-on experience with GenAI, agentic AI, and automated testing for AI systems. Curiosity and creativity to challenge assumptions and explore new approaches. Strong communication skills and a More ❯

platform and our technical approach Requirements Fluent in Python 3 Strong affinity for data, data cleansing and transformation/data wrangling and analysis, both visually and with Python (Pandas, Numpy) Confident use of REST APIs, JSON, SQL (ideally Snowflake) Strong coding standards and practices - clean code, testing, code reviews, version control (git) Experience with Machine Learning libraries would be useful More ❯

interpretability, and business relevance. Requirements Extensive experience in building and deploying Marketing Mix Models, with a strong focus on Bayesian methods. Expert-level proficiency in Python, especially with pandas, NumPy, and probabilistic programming libraries such as PyMC. Experience with R is a bonus, particularly for MMM-related workflows. Deep understanding of regression modelling, Bayesian inference, hierarchical models, and MCMC techniques. 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 ❯

Job Title: HR Data Science Intern About Us: We are a global technology company, driving energy innovation for a balanced planet. At SLB we create amazing technology that unlocks access to energy for the benefit of all. We are facing More ❯

/CPF), lint, and gate‐level simulation. Demonstrated FPGA prototyping skills: constraint management, transceiver tuning, and hardware debug in the lab. Proficiency using MATLAB/Simulink or Python/NumPy for algorithm modelling, fixed‐point analysis and test‐vector generation. Solid grounding in digital signal‐processing concepts, computer‐architecture fundamentals and semiconductor device physics. Excellent communication and cross‐functional collaboration More ❯