76 to 100 of 126 scikit-learn Jobs in the UK

algorithms, and frameworks . Proficiency in programming languages (Python, R, C/C++, Java) and secure coding practices. Hands-on experience with ML/LLM frameworks (TensorFlow, PyTorch, scikit-learn, etc.). Expertise in DevOps/CI/CD security and cloud-native architectures (containers, Kubernetes, Git). Strong knowledge of AI/ML-specific security vulnerabilities (adversarial More ❯

Spectrum, even better. You’ll need a Master’s or PhD in a quantitative field, strong Python skills, and extensive experience applying core machine learning libraries such as Scikit-learn, XGBoost, or LightGBM to structured data problems. The role may also involve developing and deploying deep learning models using frameworks like PyTorch or TensorFlow where appropriate. Experience with More ❯

Python or related language - Experience with 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 More ❯

of key machine learning models, including Gradient Boosting Machines (GBMs), Neural Networks and Large language models (LLMs). Hands-on experience with popular machine learning libraries such as Scikit-learn, XGBoost, LightGBM, TensorFlow, or PyTorch. Knowledge of AWS products and services including Sagemaker. Deep knowledge of Microsoft Excel in a commercial setting. You enjoy being Agile - you should More ❯

junior team members, and collaborating closely with engineers, PMs and analysts to deliver measurable user and business impact. We work primarily in Python and SQL, with tools like Scikit-learn, Tensorflow, PyTorch and Pandas. Our ML stack runs on AWS and Sagemaker. We value clean, documented, well-tested and reviewed code-and have the tooling and culture to More ❯

In regard to you…it would be great if you bring strong Python skills, experience with Azure ML, Docker, Git, and a passion for machine learning tools like scikit-learn, TensorFlow or PyTorch. Bonus points if you're curious about GenAI and know your way around SQL. If you're ready to build things that actually get used More ❯

benefits! In regard to you...it would be great if you bring strong Python skills, experience with Azure ML, Docker, Git, and a passion for machine learning tools like scikit-learn, TensorFlow or PyTorch. Bonus points if you're curious about GenAI and know your way around SQL. If you're ready to build things that actually get used More ❯

on areas such as robustness, explainability, or uncertainty estimation. Advanced programming and mathematical skills with Python and an experience with the standard Python data science stack (NumPy, pandas, Scikit-learn etc.). The ability to conduct and oversee complex technical research projects. A passion for leading and developing technical teams; adopting a caring attitude towards the personal and More ❯

React, TypeScript Backend: Node.js, Python, REST & GraphQL APIs Cloud & Infra: AWS (ECS, S3, Lambda), Docker, CloudFormation, Pulumi, CI/CD with GitHub Actions ML/AI: PyTorch, TensorFlow, scikit-learn, MLflow for experiment tracking, Zenml for ML pipelines Data: PostgreSQL, DynamoDB, data pipelines with Zenml (We're open to evolving the stack and expect you to influence technical More ❯

the-art areas (e.g. NLP, Transfer Learning) and modern Deep Learning algorithms (e.g. BERT, LSTM) Solid knowledge of SQL and Python's ecosystem for data analysis (Jupyter, Pandas, Scikit-Learn, Matplotlib, etc.) Understanding of model evaluation, data pre-processing techniques (standardisation, normalisation, handling missing data) Solid understanding of statistics; hypothesis testing, probability distributions, sampling techniques Private Health Care More ❯

experience Experience programming in Java, C++, Python or related language Experience 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. Amazon is an equal opportunity employer and does not discriminate More ❯

monitoring and improvement). In-depth knowledge of statistical hypothesis testing and ML modeling techniques. Experience in using Python for numerical/statistical programming (including Numpy, Pandas, and Scikit-learn). Significant experience in using SQL. Ability to communicate effectively with audiences of various backgrounds, levels, and functions. Experience in conducting and analyzing AB tests in an e More ❯

AI assurance by identifying and documenting model limitations and risks. Essential Skills & Experience Proficient in Python with a strong command of data science libraries such as pandas, NumPy, scikit-learn, and similar tools. Experience designing experiments and validating machine learning models with appropriate statistical rigor. Deep understanding of machine learning performance metrics and statistical evaluation techniques. Knowledge of More ❯

with: 3–5 years’ experience in a Data Science, AI, or ML-related role Experience with forecasting, propensity and segmentation Strong Python skills and experience with libraries like scikit-learn, pandas, and Prophet Hands-on experience developing and deploying ML models in production A track record of working across the full ML lifecycle in a fast-paced environment More ❯

with: 3–5 years’ experience in a Data Science, AI, or ML-related role Experience with forecasting, propensity and segmentation Strong Python skills and experience with libraries like scikit-learn, pandas, and Prophet Hands-on experience developing and deploying ML models in production A track record of working across the full ML lifecycle in a fast-paced environment More ❯

with: 3–5 years’ experience in a Data Science, AI, or ML-related role Experience with forecasting, propensity and segmentation Strong Python skills and experience with libraries like scikit-learn, pandas, and Prophet Hands-on experience developing and deploying ML models in production A track record of working across the full ML lifecycle in a fast-paced environment More ❯

with: 3–5 years’ experience in a Data Science, AI, or ML-related role Experience with forecasting, propensity and segmentation Strong Python skills and experience with libraries like scikit-learn, pandas, and Prophet Hands-on experience developing and deploying ML models in production A track record of working across the full ML lifecycle in a fast-paced environment More ❯

long-term internship) in data science orclimate modeling SKILLS Proficient in statistics, applied mathematics and machine learning methods; Capable of building high-performance algorithms; Proficiency in Python (e.g. scikit-learn); Fluency in English (written and verbal communication) required; Good command of one additional language (e.g. Chinese, French, Italian, German, Spanish ) is valued. MINDSET Interested in weather and natural More ❯

stratigraphy, sedimentology, or petroleum geology. Experience of working with subsurface datasets (e.g., wireline, seismic, biostratigraphy). Strong python programming skills and experience with ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Excellent communication and teamwork skills in a collaborative R&D environment. AI/ML Implementation: Design and implement AI/ML algorithms to automate and enhance geological More ❯

similar roles, with at least 2 years in fintech, payments, or financial services. Solid grounding in statistics, machine learning, and data engineering principles. Experience with Python (e.g., pandas, scikit-learn, seaborn) and SQL (Postgres preferred) for advanced data manipulation. Familiarity with the modern data stack (Databricks). Strong track record of delivering commercial and operational impact through data More ❯

Europe,andinternationally. RequiredExperience Strongknowledgeofdatamodelling,machinelearning,and/oradvanceddataanalytics. Demonstrabletrackrecordofdeliveringdataanalyticsprojectsaspartofateam. Hands-onexperiencewithcollaborativesoftwaredevelopmentandversioncontrol(preferablyGit). FamiliaritywithAgile/SCRUMmethodologies. Exposuretopre-engagementactivitiessuchasprojectscoping,technicalfeasibilityanalysis,orprototypedevelopment. Comfortablecontributingtotechnicaldiscussionsandimplementingsolutionsdefinedbyprojectleads. DesirableExperience StrongPythonexpertise. ExperiencewithGNU/Linuxenvironments. FamiliaritywithkeydatascienceandMLframeworks(e.g.,scikit-learn,PyTorch,TensorFlow,XGBoost,HuggingFace). Experienceinnaturallanguageprocessing,tabulardataanalysis,orcomputervision. SQLproficiency. Exposuretocontainerisation(Docker,Kubernetes)andcloud-nativearchitectures. ExperiencewithCI/CD,automatedtesting,anditerativeproductdevelopment. Knowledgeofgraphdatabasesandgraphanalysis. Benefits Ourclientoffersanexcitingandsupportiveenvironmentwithastrongfocusonemployeewellbeingandcareerdevelopment.Benefitsinclude: 35daysannualleave(includingpublicholidays)plusupto10daysunpaidleave. Flexibleworkingarrangementsaroundcorehours. Privatehealthinsuranceandpensionscheme. Contributiontogymmembership. More ❯

business. Machine Learning Engineer, key skills: Significant experience working as a Data Scientist/Machine Learning Engineer Solid knowledge of SQLandPython's ecosystem for data analysis (Jupyter, Pandas, Scikit Learn, Matplotlib). GCP, VertexAI experience is desirable (developing GCP machine learning services) Timeseries forecasting Solid understanding of computer science fundamentals, including data structures, algorithms, data modelling and software More ❯

Senior Data Scientist - Consumer Lending Hybrid working - London Offices Negotiable to £75,000 DEO + Benefits Reference - J12979 Our client is an innovative UK based consumer finance business, with a digital credit card launched in 2018, and a pipeline of More ❯

background with direct experience in machine learning applications. Proven track record leading teams – balancing delivery with career growth and mentorship. Proficiency in modern ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn) and cloud platforms. Comfortable working across the full lifecycle: from research prototypes to production-scale systems. Excellent communication skills and a collaborative mindset. Why apply? This is an More ❯

background with direct experience in machine learning applications. Proven track record leading teams – balancing delivery with career growth and mentorship. Proficiency in modern ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn) and cloud platforms. Comfortable working across the full lifecycle: from research prototypes to production-scale systems. Excellent communication skills and a collaborative mindset. Why apply? This is an More ❯