1 to 25 of 31 SciPy Jobs in the UK excluding London

field. Professional experience with collaborative software development. Deep understanding of Python. Familiarity with Linux, bash, and the command line. Experience with modern statistical machine learning and AI, including Numpy, Scipy, and Pandas. Ability to write logical, consistent, self-explanatory code. Understanding of software design patterns, SOLID and DRY principles. Experience with Git/GitHub and best practices. Knowledge of the More ❯

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, dbt) Track record More ❯

interaction with the models Testing and documentation Requirements: Experienced Python developer Experience utilising machine learning libraries such as (in order of importance) TensorFlow, HuggingFace, scikit-learn, PyTorch, Pandas, NumPy, SciPy Experience with AWS (principally EC2, S3, SageMaker) or Azure/GCP equivalents Some experience of designing, developing and deploying scalable infrastructure (eg Apache Airflow, Luigi or other cluster management software More ❯

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-paced front More ❯

experience or keen interest Data pipelines and big data tech Docker: both building but running too Wide AWS and infrastructure knowledge, including production support Scientific computing e.g. Numpy/scipy/pandas Just state the word 'Salmon' anywhere in your application, just to prove you can read a job advert. We aim to improve all our colleagues' abilities and careers More ❯

accountable. These are ourvaluesand influence everything we do. Preferred Qualifications Familiarity building scalable services in a microservices architecture. Familiarity with statistical tools such as SAS, or Python (with NumPy, SciPy, Pandas) Familiarity with public cloud platforms, such as AWS, Azure, or GCP. Strong testing automation experience, preferably in *unit frameworks Diverse and Inclusive At SAS, it’s not about fitting More ❯

of professional experience in software engineering Strong proficiency in Python and one additional language (e.g. C++, Java, Scala) Experience with ML frameworks (e.g. PyTorch, TensorFlow), and scientific libraries (NumPy, SciPy, scikit-learn) Familiarity with audio data (or video), able to handle large binary files Proven experience in at least one of: ML model deployment, ML Ops, AI agents, or LLM More ❯

Social network you want to login/join with: Responsibilities: Join our dynamic team focusing on the FICC Emerging Markets deliveries, specialising in algorithm development and strategic framework creation. Play a crucial role in the development of the next-generation More ❯

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 ❯

and Reinforcement Learning techniques. Practical exposure to GenAI projects and related frameworks (RAG apps, vector DBs, LangChain, LlamaIndex, agentic frameworks, ...) Advanced knowledge of Python and machine learning frameworks (SciPy, Scikit-learn, TensorFlow, PyTorch, pyMC, pgmpy, ...) Hands-on experience with one or more cloud computing platforms (Azure - preferred, AWS, GCP). Understanding of the whole ML lifecycle and experience More ❯

Technical Expertise: A deep command of Python, experience working closely with hardware plus proven experience developing scientific or analytical applications using numerical and engineering-oriented Python tools (e.g., NumPy, SciPy). Location: Cambridge Position: Senior Software Engineer Salary: Up to £100K Seniority level Mid-Senior level Employment type Full-time Job function Industries: Software Development and Appliances, Electrical, and Electronics More ❯

neural deep learning methods and machine learning - Experience with prompting techniques for LLMs PREFERRED QUALIFICATIONS - Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc. - Experience with large scale distributed systems such as Hadoop, Spark etc. - PhD in math/statistics/engineering or other equivalent quantitative discipline - Experience with conducting research in a More ❯

bottlenecks in existing code and algorithms to ensure high efficiency and scalability What we're looking for At least 5+ years of experience within the PyData stack (NumPy, Pandas, SciPy, etc.), ideally in a research-oriented environment Strong background in data manipulation, data processing, and visualizations at a data-rich organization Strong communication skills, with the ability to convey technical More ❯

Neural Networks) on small and large datasets. Strong experience in at least one ML framework (PyTorch/TensorFlow/Jax) and robust experience in Python data science ecosystem (Numpy, SciPy, Pandas, etc.) Experience using a cloud computing service to reduce runtime to train and evaluate deep learning models PhD in Computer Science, Applied Mathematics, quantitative disciplines with strong focus in More ❯

or PhD degree in a quantitative field. • Proven experience of large-scale data analysis and hypothesis testing. • Strong proficiency in statistical analysis and predictive modeling. • Proficient in Python (pandas, scipy, numpy, scikit-learn) or R (tidyverse/data.table), along with SQL. • Excellent problem-solving skills and attention to detail. • Strong communication skills with the ability to present complex data insights More ❯

quantitative background (e.g., Engineering, Mathematics, Physics, or similar fields). Proficiency with data manipulation and modelling tools, e.g. pandas, statsmodels, R. Experience with scientific computing and tooling, e.g. NumPy, SciPy, R, Matlab, Mathematica, BLAS. Self-starter with ability to work autonomously and efficiently manage projects end-to-end. Excellent communication skills, with the ability to adjust your communication style and More ❯

Data Science or AI domains Proven track record of leading complex AI projects in an agile environment Strong technical proficiency with modern ML tools and frameworks: PyTorch, TensorFlow, SparkMLLib, SciPy, Scikit-Learn, NLTK (etc) MLflow or similar ML lifecycle tools Cloud platforms (AWS/Azure/GCP) Experience with AI governance and responsible AI practices Understanding of public sector data More ❯

Data Science or AI domains Proven track record of leading complex AI projects in an agile environment Strong technical proficiency with modern ML tools and frameworks: PyTorch, TensorFlow, SparkMLLib, SciPy, Scikit-Learn, NLTK (etc) MLflow or similar ML lifecycle tools Cloud platforms (AWS/Azure/GCP) Experience with AI governance and responsible AI practices Understanding of public sector data More ❯

and scipy. Collaborate with our data scientists and domain experts to understand project requirements and design optimised AI solutions. Preprocess and analyse visual data using OpenCV, scikit-learn, and scipy to extract meaningful insights. Train and fine-tune AI models using TensorFlow/Keras, PyTorch, PaddlePaddle, and other relevant frameworks to achieve high accuracy. Optimize AI models using OpenVINO for … experience as an AI Engineer or similar roles. Strong proficiency in Python/C++ for AI model development and inference. Experience with OpenVINO, OpenCV, AWS, CVAT, scikit-learn, and scipy for visual AI applications. Proficiency in TensorFlow/Keras, PyTorch, and PaddlePaddle for model training and optimisation. Strong analytical and problem-solving skills with the ability to handle large-scale More ❯

learn, and scipy. Collaborate with data scientists and domain experts to understand project requirements and design optimized AI solutions. Preprocess and analyze visual data using OpenCV, scikit-learn, and scipy to extract meaningful insights. Train and fine-tune AI models using TensorFlow/Keras, PyTorch, PaddlePaddle, and other relevant frameworks to achieve high accuracy. Optimize AI models using OpenVINO for … experience as an AI Engineer or similar roles. Strong proficiency in Python/C++ for AI model development and inference. Experience with OpenVINO, OpenCV, AWS, CVAT, scikit-learn, and scipy for visual AI applications. Proficiency in TensorFlow/Keras, PyTorch, and PaddlePaddle for model training and optimization. Strong analytical and problem-solving skills with the ability to handle large-scale More ❯

or PhD degree in a quantitative field. Proven experience of large-scale data analysis and hypothesis testing. Strong proficiency in statistical analysis and predictive modeling. Proficient in Python (pandas, scipy, numpy, scikit-learn) or R (tidyverse/data.table), along with SQL. Excellent problem-solving skills and attention to detail. Strong communication skills with the ability to present complex data insights More ❯

on highly visible, large-scale projects. What you'll bring to the role Strong grounding in ML approaches, techniques, and frameworks Proficiency in Python, Pandas, TensorFlow, Scikit-learn, Numpy, SciPy Experience deploying models to the cloud and working with Azure (Azure DevOps, Azure ML, Azure SQL, ADF, etc.) Ability to work with databases such as SQL Server, NoSQL, etc. Experience More ❯

techniques, including sampling methods, regression, properties of distributions, weighting sample-based data, and proper use of statistical tests in real-world applications. Proficiency with Python libraries such as NumPy, SciPy, Pandas, scikit-learn, and others related to data and machine learning. Working knowledge of SQL, data structures, and databases (Snowflake is desirable). This organization is pragmatic and humble, seeking More ❯

Providing relevant insights Advanced statistical and analytical techniques and concepts sampling methods, Regression Properties of distributions Weighting sample-based data Statistical tests proper usage Real-world applications. Python - NumPy, SciPy, Pandas, MLlib, scikit-learn, and other common data and machine learning related libraries Working knowledge of SQL, data structures and databases (Snowflake - desirable) This is a pragmatic and humble organisation More ❯

Providing relevant insights Advanced statistical and analytical techniques and concepts sampling methods, Regression Properties of distributions Weighting sample-based data Statistical tests proper usage Real-world applications. Python - NumPy, SciPy, Pandas, MLlib, scikit-learn, and other common data and machine learning related libraries Working knowledge of SQL, data structures and databases (Snowflake - desirable) This is a pragmatic and humble organisation More ❯