1 to 25 of 36 SciPy Jobs in the UK excluding London

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 More ❯

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 More ❯

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 More ❯

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 More ❯

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 More ❯

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 More ❯

problems, ideally including Large Language Models Proficiency in Python, particularly with machine learning and data science libraries such as PyTorch, scikit-learn, numpy and scipy Good communication and interpersonal skills Experience working with large-scale data processing systems such as Spark and Hadoop Experience in software development in agile environments More ❯

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 ❯

Proficient with Gurobi Optimizer (or equivalent like CPLEX, CBC). Understanding of electricity system balancing, dispatch processes, and control systems. Python ecosystem (NumPy, Pandas, SciPy, Pyomo, etc.) Gurobi Optimizer (for LP, QP, MILP, etc.) Contract Details: Duration: 6 months (View for Extension) Day Rate: Up to £500 per day (Inside More ❯

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 More ❯

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 More ❯

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 More ❯

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 More ❯

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 More ❯

problems, ideally including Large Language Models Proficiency in Python, particularly with machine learning and data science libraries such as PyTorch, scikit-learn, numpy and scipy Good communication and interpersonal skills Experience working with large-scale data processing systems such as Spark and Hadoop Experience in software development in agile environments More ❯

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 More ❯

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 More ❯

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 More ❯

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 More ❯

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 More ❯

distributions, weighting sample-based data, and proper use of statistical tests. Real-world applications of these techniques. Proficiency in 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 experience is desirable). This More ❯

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 More ❯

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 More ❯

with neural deep learning methods and machine learning 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. Our inclusive culture empowers Amazonians to deliver the best results for our customers. More ❯

with neural deep learning methods and machine learning. 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. Our inclusive culture empowers Amazonians to deliver the best results for our customers. More ❯