1 to 25 of 157 Permanent NumPy Jobs in the UK

C#, TypeScript, JavaScript Machine Learning: TensorFlow, PyTorch, Scikit-learn GenAI/LLMs: OpenAI API, Hugging Face Transformers, LangChain, Langraph, RAG pipelines Data & Analytics: Pandas, NumPy, Spark, Databricks, Hadoop, Vector Databases, Snowflake Model Deployment: MLflow, FastAPI, Flask, Docker, Kubernetes Cloud & Infrastructure: AWS, Azure, GCP CI/CD pipelines (GitLab, Jenkins) Desirable ...

C#, TypeScript, JavaScript Machine Learning: TensorFlow, PyTorch, Scikit-learn GenAI/LLMs: OpenAI API, Hugging Face Transformers, LangChain, Langraph, RAG pipelines Data & Analytics: Pandas, NumPy, Spark, Databricks, Hadoop, Vector Databases, Snowflake Model Deployment: MLflow, FastAPI, Flask, Docker, Kubernetes Cloud & Infrastructure: AWS, Azure, GCP CI/CD pipelines (GitLab, Jenkins) Desirable ...

/Computer Science Academic background 3-5 years of experience with Python (writing and managing code releases) Familiarity with numerical Python libraries, e.g. Pandas, Numpy Firm understanding of version control, testing, and continuous integration Understanding and appreciation for best practices Experience working with SQL databases and Sqlalchemy desired We encourage ...

/Computer Science Academic background 3-5 years of experience with Python (writing and managing code releases) Familiarity with numerical Python libraries, e.g. Pandas, Numpy Firm understanding of version control, testing, and continuous integration Understanding and appreciation for best practices Experience working with SQL databases and Sqlalchemy desired We encourage ...

Experience with distributed systems, parallel computing, and high-performance processing of large datasets. Strong experience in data pipelines, working with tools such as Pandas, NumPy, and SQL/NoSQL databases. Proven experience working in fast-paced environments, ideally within trading, financial services, or high-frequency environments. Proficiency in developing RESTful ...

Experience with distributed systems, parallel computing, and high-performance processing of large datasets. Strong experience in data pipelines, working with tools such as Pandas, NumPy, and SQL/NoSQL databases. Proven experience working in fast-paced environments, ideally within trading, financial services, or high-frequency environments. Proficiency in developing RESTful ...

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 ...

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 ...

Computer Science, Software Engineering or a related field. 2. Experience with image processing libraries (e.g. OpenCV, PIL, scikit-image) or numerical analysis (NumPy, SciPy). 3. Solid understanding of React/JavaScript/Typescript for web or mobile app development. Desirable skills/requirements 4. Experience with cloud/server ...

comfortable with ambiguity and will want to dive deep and fix problems at scale. The environment looks a bit like this Python (pandas, numpy, scipy, PySpark) SQL AWS or GCP (BigQuery/RedShift/Snowflake) Spark/Databricks Airflow/Dagster ...

comfortable with ambiguity and will want to dive deep and fix problems at scale. The environment looks a bit like this 👇 👉 Python (pandas, numpy, scipy, PySpark) 👉 SQL 👉 AWS or GCP (BigQuery/RedShift/Snowflake) 👉 Spark/Databricks 👉 Airflow/Dagster ...

understanding the limitations of the language) and in building data pipelines and ML models using modern libraries across multiple domains: Data science stack: NumPy, pandas/polars, scikit-learn, XGBoost, LightGBM Deep learning: PyTorch, JAX Statistical programming: NumPyro, PyMC Data skills: Proficient in SQL, with the ability to write efficient ...

understanding the limitations of the language) and in building data pipelines and ML models using modern libraries across multiple domains: Data science stack: NumPy, pandas/polars, scikit-learn, XGBoost, LightGBM Deep learning: PyTorch, JAX Statistical programming: NumPyro, PyMC Data skills: Proficient in SQL, with the ability to write efficient ...

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 ...

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 ...

will be able to develop the prototypes of the models, and do some feature engineering. The environment looks a bit like this 👇 👉 Python (pandas, numpy, scipy, PySpark) 👉 SQL 👉 AWS or GCP (BigQuery/RedShift/Snowflake ...

high-performance systems Background in trading systems, market data, or quantitative infrastructure Solid understanding of concurrency, algorithms, OOP, and system design Experience with Python (NumPy/Pandas) in a scientific or trading context Comfortable working in Unix/Linux environments Experience with SQL/NoSQL/tick databases ...

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 ...

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 ...

Core Technical Skills Skill Area Requirements Programming Strong proficiency in Python for data manipulation and scripting. Familiarity with standard Python data libraries (e.g., Pandas, NumPy). Database Expert-level proficiency in SQL (Structured Query Language). Experience writing complex joins, stored procedures, and performing performance tuning. Big Data Concepts Foundational ...

Core Technical Skills Skill Area Requirements Programming Strong proficiency in Python for data manipulation and scripting. Familiarity with standard Python data libraries (e.g., Pandas, NumPy ). Database Expert-level proficiency in SQL (Structured Query Language). Experience writing complex joins, stored procedures, and performing performance tuning. Big Data Concepts Foundational ...

performance over time. Required Skills and Qualifications Technical Expertise (The Core) Programming: Expert proficiency in Python and its core data science libraries: Pandas, NumPy, and SciPy. Machine Learning: Deep, practical experience with popular ML frameworks and libraries: scikit-learn, TensorFlow, or PyTorch. Statistics & Math: Strong foundation in statistical modeling, probability ...

performance over time. Required Skills and Qualifications Technical Expertise (The Core) Programming: Expert proficiency in Python and its core data science libraries: Pandas, NumPy, and SciPy . Machine Learning: Deep, practical experience with popular ML frameworks and libraries: scikit-learn, TensorFlow, or PyTorch . Statistics & Math: Strong foundation in statistical ...

Experience with recommender systems, personalisation, or deep learning is desirable but not essential. Solid Python skills and experience with ML libraries such as pandas, numpy, scipy, scikit-learn, TensorFlow or PyTorch. Experience working across cloud environments (GCP, AWS, or Azure) and analytics platforms such as Dataiku. Good understanding of MLOps ...

your Python skills by building a car price prediction app using Python and Streamlit. Step 6 – Python for Data Learn essential Python libraries like NumPy, Pandas, and Matplotlib for data manipulation and visualisation. Step 7 – AI Sentiment Analysis Project Work with Hugging Face to build a sentiment analysis classifier using ...