10 of 10 Permanent NumPy Jobs in Central London

and design principles (SOLID) Excellent understanding of commercial development practices such as testing, documentation, package management and SDLC Excellent understanding of python for numerical programs. In particular, pandas and numpy are a must Excellent problem-solving skills Strong communication skills (the role will involve explaining complex algorithms to colleagues with varying technical and mathematical experience) Desirable Knowledge of UNIX & AWS More ❯

in recommendation systems and deep learning architectures. Strong understanding of two-tower neural networks, embedding techniques, and ranking models. 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. Experience with ML Ops, including model deployment, monitoring, and retraining pipelines. Ability to work More ❯

Skills and Experience: Proven ability to solve complex, real-world problems through data science and analytics. Experience coaching and reviewing work of junior team members. Strong Python skills (pandas, numpy, scikit-learn) and a solid grounding in probability and statistics. Deep knowledge of machine learning methods and their practical application. Experience managing multiple end-to-end data science projects across More ❯

Skills and Experience: Proven ability to solve complex, real-world problems through data science and analytics. Experience coaching and reviewing work of junior team members. Strong Python skills (pandas, numpy, scikit-learn) and a solid grounding in probability and statistics. Deep knowledge of machine learning methods and their practical application. Experience managing multiple end-to-end data science projects across More ❯

Technical Expertise: Solid experience in Python programming, particularly using data manipulation and processing libraries such as Pandas, NumPy, and Apache Spark. Hands-on experience with open-source data frameworks like Apache Spark, Apache Kafka, and Apache Airflow. Strong proficiency in SQL, including advanced query development and performance tuning. Good understanding of distributed computing principles and big data ecosystems. Familiar with More ❯

Technical Expertise: Solid experience in Python programming, particularly using data manipulation and processing libraries such as Pandas, NumPy, and Apache Spark. Hands-on experience with open-source data frameworks like Apache Spark, Apache Kafka, and Apache Airflow. Strong proficiency in SQL, including advanced query development and performance tuning. Good understanding of distributed computing principles and big data ecosystems. Familiar with 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 ❯

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 ❯

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 ❯

analyze large datasets and derive actionable insights for equity portfolios. Build and maintain data pipelines, ensuring data accuracy, reliability, and scalability. Use Python (and related libraries such as Pandas, NumPy, etc.) to develop and automate tasks, backtest strategies, and optimize performance. Work with portfolio managers to create tools for portfolio construction, risk analysis, and scenario modeling. Ensure seamless integration of … Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, Physics, Finance, or a related field. Strong proficiency in Python, with a deep understanding of libraries like Pandas, NumPy, and others for data manipulation and analysis. Solid understanding of financial markets, particularly equities, and portfolio management concepts. Knowledge of databases (SQL, NoSQL) and experience in working with large datasets. More ❯