1 to 25 of 73 NumPy Jobs in the City of London

Markets, especially in a Hedge Fund, Trading Firm, and/or working with Quant Trading Technology. Expertise in Python, including popular Python libraries for data wrangling, such as Pandas, NumPy, and SQLAlchemy. Experience working with traditional SQL databases (e.g. PostgreSQL, MySQL, SQL Server) and cloud data warehouses (e.g. Snowflake, Databricks, BigQuery, Redshift). Experience with time-series data, and/ More ❯

Markets, especially in a Hedge Fund, Trading Firm, and/or working with Quant Trading Technology. Expertise in Python, including popular Python libraries for data wrangling, such as Pandas, NumPy, and SQLAlchemy. Experience working with traditional SQL databases (e.g. PostgreSQL, MySQL, SQL Server) and cloud data warehouses (e.g. Snowflake, Databricks, BigQuery, Redshift). Experience with time-series data, and/ More ❯

and system performance • Implement robust risk management and stress-testing tools 🎯 What You Bring • 5+ years Java (OOP, low-latency systems) • 4+ years FX or Crypto trading experience • Python (NumPy, Pandas, SciPy) • SQL or time-series DBs • Linux & distributed systems expertise • Strong communication & market intuition ✨ Bonus Skills • KDB+/Q, Haskell, or other functional languages • Machine learning (scikit-learn, etc. More ❯

and system performance • Implement robust risk management and stress-testing tools 🎯 What You Bring • 5+ years Java (OOP, low-latency systems) • 4+ years FX or Crypto trading experience • Python (NumPy, Pandas, SciPy) • SQL or time-series DBs • Linux & distributed systems expertise • Strong communication & market intuition ✨ Bonus Skills • KDB+/Q, Haskell, or other functional languages • Machine learning (scikit-learn, etc. More ❯

reliability and innate curiosity to learn new things Preferred qualifications Background in traditional finance or digital assets, ideally in trading domain Hands-on experience with Python libraries and frameworks (NumPy, Pandas, Airflow, FastAPI, Flask, SQLAlchemy) Highly proficient in asynchronous, event driven distributed systems Working knowledge of cloud-native architectures, GCP preferred Experience in Go and working with real-time data More ❯

reliability and innate curiosity to learn new things Preferred qualifications Background in traditional finance or digital assets, ideally in trading domain Hands-on experience with Python libraries and frameworks (NumPy, Pandas, Airflow, FastAPI, Flask, SQLAlchemy) Highly proficient in asynchronous, event driven distributed systems Working knowledge of cloud-native architectures, GCP preferred Experience in Go and working with real-time data More ❯

the OpenAPI specification and code generation toolsets for API development. Some experience with Python, modern development techniques, and design patterns. Experience in data science tools and ML tools (e.g., NumPy, pandas, scikit-learn, PyTorch) and open-source contributions (especially Python-based) would be a bonus. Familiarity with CUDA, GPU-based computations, end-to-end neural network training, MLOps, and academic More ❯

the OpenAPI specification and code generation toolsets for API development. Some experience with Python, modern development techniques, and design patterns. Experience in data science tools and ML tools (e.g., NumPy, pandas, scikit-learn, PyTorch) and open-source contributions (especially Python-based) would be a bonus. Familiarity with CUDA, GPU-based computations, end-to-end neural network training, MLOps, and academic More ❯

of ML systems in production. What We’re Looking For 3+ years of experience in Data Science. Strong proficiency in Python and experience with ML libraries/frameworks (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch). Hands-on experience implementing end-to-end ML pipelines (data ingestion, training, validation, serving). Familiarity with ML workflow orchestration tools (Airflow, Prefect, Kubeflow) and More ❯

Requirements: 1st class - 2;1 Degree in Comp Sci or STEM subject from a Top ranked University 3+ years of experience in Python development Tech: Python, FastAPI, Pydantic, PostgreSQL, Numpy, Pandas, AWS DevOps tools: Kubernetes, Docker,Terraform, Jenkins Very strong software engineering principles Enthusiasm for startup environment and cross-functional teams Passion for automation and data infrastructure More ❯

Requirements: 1st class - 2;1 Degree in Comp Sci or STEM subject from a Top ranked University 3+ years of experience in Python development Tech: Python, FastAPI, Pydantic, PostgreSQL, Numpy, Pandas, AWS DevOps tools: Kubernetes, Docker,Terraform, Jenkins Very strong software engineering principles Enthusiasm for startup environment and cross-functional teams Passion for automation and data infrastructure More ❯

production, with at least 3+ years leading data science teams. Fluent in Python and a strong interest in general software engineering principles. You have worked with common python frameworks (Numpy, Pandas...) Demonstrated expertise with agentic AI systems , including orchestration frameworks (LangGraph preferred, LangChain or similar also considered). Strong foundation in classical machine learning and applied modeling techniques , including regression More ❯

the OpenAPI specification and code generation toolsets for API development. Some experience with Python, modern development techniques, and design patterns. Experience in data science tools and ML tools (e.g., NumPy, pandas, scikit-learn, PyTorch) and open-source contributions (especially Python-based) would be a bonus. Familiarity with CUDA, GPU-based computations, end-to-end neural network training, MLOps, and academic More ❯

the OpenAPI specification and code generation toolsets for API development. Some experience with Python, modern development techniques, and design patterns. Experience in data science tools and ML tools (e.g., NumPy, pandas, scikit-learn, PyTorch) and open-source contributions (especially Python-based) would be a bonus. Familiarity with CUDA, GPU-based computations, end-to-end neural network training, MLOps, and academic More ❯

Requirements Bachelors or higher in computer science or equivalent Strong Python knowledge Strong interest and knowledge of financial markets and instruments Experience in data analysis techniques and libraries like NumPy, SciPy, and Pandas Solid understanding of mathematics, including statistics, asset pricing theory, and optimization algorithms More ❯

Requirements Bachelors or higher in computer science or equivalent Strong Python knowledge Strong interest and knowledge of financial markets and instruments Experience in data analysis techniques and libraries like NumPy, SciPy, and Pandas Solid understanding of mathematics, including statistics, asset pricing theory, and optimization algorithms More ❯

platforms to provide enhances analytics and tooling for Traders and Front Office teams To be a successful applicant, you will need: Extensive experience of Software Engineering using Python (Pandas, Numpy, FastAPI) to a high standard, building highly performant systems and platforms used by Traders Experience working in a Hedge Fund, Trading firm, or similar working directly with front-office stakeholders More ❯

platforms to provide enhances analytics and tooling for Traders and Front Office teams To be a successful applicant, you will need: Extensive experience of Software Engineering using Python (Pandas, Numpy, FastAPI) to a high standard, building highly performant systems and platforms used by Traders Experience working in a Hedge Fund, Trading firm, or similar working directly with front-office stakeholders 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 ❯

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 ❯

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 ❯

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 ❯