1 to 25 of 67 Remote/Hybrid scikit-learn Jobs

Data Scientist, Hands-on experience deploying ML models to production, not just research-level familiarity, Strong proficiency in Python (NumPy, pandas, scikit-learn, matplotlib, pytorch), Understanding of Windows or Linux software development platforms Excellent command of English – both written and spoken (international client communication, presentations), Expertise ...

another STEM-related discipline. Desirable Skills Experience with cloud platforms such as AWS, Azure or GCP . Experience with Pandas, NumPy and Scikit-learn . Knowledge of data visualisation tools such as Power BI or Tableau. Experience with Git/version control. Exposure to Generative AI, LLMs ...

machine learning, or statistical modeling, Practical experience with ML model deployment (on cloud or on-premise), Solid programming skills in Python (NumPy, pandas, scikit-learn, matplotlib, PyTorch or TensorFlow), Understanding of Windows or Linux software development platforms Good understanding of statistics and data preparation, Working knowledge ...

work on projects independently and own deliverables. Strong proficiency in Python for data manipulation, analysis, visualisation and data science (e.g., Pandas, NumPy, Scikit-learn). Proficiency in data querying languages (e.g., SQL). Solid understanding of software engineering best practices (version control, unit testing, code review, etc.). ...

work on projects independently and own deliverables. Strong proficiency in Python for data manipulation, analysis, visualisation and data science (e.g., Pandas, NumPy, Scikit-learn). Proficiency in data querying languages (e.g., SQL). Solid understanding of software engineering best practices (version control, unit testing, code review, etc.). ...

Community of Practice. Experience Required Essential Strong Python programming and hands-on experience with core ML/AI libraries (for example scikit-learn, TensorFlow, PyTorch). Practical experience developing, training and evaluating machine learning, NLP and predictive models. Experience deploying AI/ML in the cloud, particularly Microsoft ...

coaching junior data scientists/analysts. Experience in reviewing code and documentation to a high standard. Experience in using Python (pandas, numpy, scikit-learn). End-to-end experience of managing multiple data science and analytics projects in different industries and with different types of data (text, numerical ...

work on projects independently and own deliverables. Strong proficiency in Python for data manipulation, analysis, visualisation and data science (e.g., Pandas, NumPy, Scikit-learn). Proficiency in data querying languages (e.g., SQL). Solid understanding of software engineering best practices (version control, unit testing, code review, etc.). ...

work on projects independently and own deliverables. Strong proficiency in Python for data manipulation, analysis, visualisation and data science (e.g., Pandas, NumPy, Scikit-learn). Proficiency in data querying languages (e.g., SQL). Solid understanding of software engineering best practices (version control, unit testing, code review, etc.). ...

work on projects independently and own deliverables. Strong proficiency in Python for data manipulation, analysis, visualisation and data science (e.g., Pandas, NumPy, Scikit‐learn). Proficiency in data querying languages (e.g., SQL). Solid understanding of software engineering best practices (version control, unit testing, code review, etc.). ...

models that drive measurable business value. Technical Proficiency: Strong expertise in Python and SQL. Deep familiarity with the Python data stack (pandas, NumPy, scikit-learn) and standard ML frameworks (such as PyTorch, XGBoost, or LightGBM). Engineering Rigor: Proven ability to build for production. Experience working in cloud ...

following areas would be highly beneficial: Machine Learning and AI Engineering Generative AI and Large Language Models Prompt engineering and context engineering scikit-learn, PyTorch or TensorFlow LangChain or similar AI frameworks Cloud data platforms and services across AWS, Azure or GCP Data warehouses and modern data platforms ...

unstructured data, especially large-scale text or content datasets. Familiarity with common data science and machine learning tools such as Pandas, NumPy, SciPy, Scikit-learn, PyTorch, TensorFlow, or Matplotlib. The ability to translate complex and ambiguous requirements into practical, measurable, data-driven solutions, with strong analytical thinking, problem ...

client projects Requirements 5+ years of experience in machine learning engineering or applied ML research Strong proficiency in Python, PyTorch or TensorFlow, and Scikit-learn Experience deploying ML models at scale using Docker, Kubernetes, or serverless Deep understanding of ML fundamentals: optimisation, regularisation, evaluation metrics Experience with cloud ...

project objectives. Masters degree in a STEM field (maths, science, engineering etc.) or equivalent Strong programming skills in Python (e.g., NumPy, Pandas, scikit-learn, TensorFlow/PyTorch). Demonstrable experience in creating and developing Python libraries. Demonstrable experience designing, implementing and training machine learning models from scratch. Strong ...

leading ML/AI technical initiatives across multiple teams Strong experience with cloud platforms (AWS, Azure, GCP) Experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and Gen AI/Agentic frameworks (LangGraph, LangChain, VectorDBs, RAG) Understanding of responsible AI practices, including guardrails, hallucination mitigation, and output quality management ...

data science expertise Machine learning and AI delivery Generative AI/LLM experience Strong Python skills and familiarity with core libraries (pandas, NumPy, scikit‐learn) Deep learning and NLP stacks (PyTorch, HuggingFace Transformers) MLOps and model operationalisation Additional Requirements: Security clearance (SC/BPSS) Familiarity with regulated industries ...

design end-to-end models, write production-quality code, and make independent modelling and architecture decisions. Advanced Python and SQL, including pandas, scikit-learn, and XGBoost/LightGBM. Experience in at least two of the following: forecasting, segmentation, recommender systems, ranking, or behavioural modelling. Proven delivery ...

Strong commercial experience developing machine learning solutions in Python Solid understanding of the Python ML ecosystem including libraries such as NumPy, pandas, and scikit learn, with exposure to PyTorch or TensorFlow Experience building and deploying containerised services and APIs Working knowledge of SQL and data driven application development ...

that deliver measurable business impact Technical Mastery: High proficiency in Python and SQL. Expert-level experience with the Python data stack (pandas, NumPy, scikit-learn) and at least one major ML framework (such as PyTorch or XGBoost/LightGBM) Systemic Problem Solving: Ability to work on unique issues ...

experience with SQL for data processing and analytics. Strong programming skills in Python , with experience using data science libraries such as Pandas, Numpy, Scikit-learn, and Keras/PyTorch . Experience with Databricks and Spark for data manipulation and querying. Prior experience in the retail industry, with ...

Proven track record of designing, developing, and deploying AI systems in production environments.· Proficient in Python and key ML libraries (e.g. PyTorch, PySpark, scikit-learn, Hugging Face Transformers).· Hands-on experience with modern data platforms and AI tooling such as Azure ML, Databricks, MLflow, LangChain, LangGraph.· Proven ...

subject. Physical sciences or mathematics are preferred. Strong Python skills and competency across the Python data science ecosystem such as pandas, numpy and scikit-learn, or a highly transferable equivalent. Experience working with LLMs and agentic AI systems, including harnesses, RAG, context engineering and evaluations. Experience working safely ...

explainability techniques Applying machine learning techniques within computer vision or natural language processing Using Python data science and visualisation libraries such as pandas, scikit-learn, statsmodels, matplotlib or seaborn, alongside deep learning frameworks such as TensorFlow or PyTorch Working with large datasets, data analysis, data warehouses, big data ...

model prototyping to production deployment, integration, and ongoing monitoring. You are proficient in Python and its data/ML ecosystem (e.g. pandas, scikit-learn, PyTorch, TensorFlow), and you can apply statistical and machine learning techniques confidently in real-world settings. You have deployed models into live systems ...