21 of 21 Remote/Hybrid scikit-learn Jobs in London

setting. Education: Relevant Software Engineering/Computer Science degree. Technical Skills Programming Languages: Python, Java, C++, 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 ...

GenAI: Experience with LLM APIs and Context Engineering (constructing prompts, managing context windows, evaluating behaviour). Engineering & Stack: Python: Expert level (Pandas, NumPy, Scikit-Learn). Data Engineering: Strong SQL skills and experience building data pipelines. Experience: Education: Degree in a quantitative field (Statistics, Mathematics, Computer Science, etc. ...

patterns, demand profiles, and commercial optimisation. Required Skills and Experience Technical Skills Proficiency in Python and associated data science libraries (NumPy, Pandas, SciPy, scikit‐learn, PyTorch/TensorFlow). Strong experience with time‐series modelling (ARIMA, Prophet, LSTMs or similar). Understanding of optimisation methods (linear, mixed‐integer ...

feature effectiveness. Ability to navigate large, complex, or ambiguous datasets and translate analysis into clear, actionable insights. Experience using common ML libraries (e.g. scikit-learn, PyTorch, TensorFlow, or similar). Exposure to cloud-based data or ML platforms (AWS, GCP, Azure or similar). Strong data visualisation ...

such as NLP, computer vision, audio, graphs, time-series or tabular data Strong Python skills and experience with common libraries (e.g. pandas, NumPy, scikit-learn, PyTorch, Transformers, statsmodels, PyMC) Understanding of software engineering and ML best practices, including version control, packaging and model deployment Experience training and deploying ...

years' experience as a data scientist in industry or related environments. Proficiency in Python and common ML/data libraries (e.g., pandas, numpy, scikit-learn, PyTorch, transformers). Understanding of software and ML engineering best practices (git, package development, model deployment). Experience with cloud platforms, particularly ...

junior colleagues and share learnings across the team. Requirements: Hands-on experience developing and deploying ML models in Python using frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow. Strong experience with AWS ML services (SageMaker, Lambda, S3) in production environments. Strong experiment design skills: hypothesis formulation ...

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 practices ...

solutions Implement experiment tracking and monitoring Collaborate with data scientists and engineers What We're Looking For: Proficiency in Python and ML frameworks (scikit-learn, PyTorch, TensorFlow) Hands-on experience with AWS ML services (SageMaker, Lambda) Familiarity with containerisation (Docker) and orchestration (Kubernetes/ECS) Knowledge of LLMOps ...

junior data scientists and help shape AI best practice Requirements Strong experience in AI, machine learning and statistics Python expertise (e.g. pandas, NumPy, scikit-learn, PyTorch, transformers) Experience deploying models and working with cloud platforms (AWS preferred) Ability to communicate complex technical concepts clearly Desirable AWS services (SageMaker ...

years' experience in ML/AI engineering or data science roles (senior level). Hands-on experience with Python ML frameworks (scikit-learn, PyTorch, TensorFlow, XGBoost). Experience with AWS ML services (SageMaker, Lambda, S3) and MLOps/LLMOps tooling (MLflow, Weights & Biases, DVC). Proven track record ...

engineers to productionise models Communicate insights to technical and non-technical stakeholders Mentor junior team members Skillset: Strong Python and ML libraries (scikit-learn, PyTorch, pandas, NumPy) Experience with AWS cloud services (SageMaker, Lambda, S3) Familiarity with MLOps tools (MLflow, Weights & Biases) Knowledge of NLP, computer vision ...

stakeholders Mentor junior engineers and contribute to team best practices This role is for you if you have: Strong Python ML experience (e.g. scikit-learn, XGBoost, PyTorch, or TensorFlow) Production experience with AWS ML services (e.g. SageMaker, Lambda, S3) Proven ability to move models from experimentation into live ...

experience delivering AI/ML projects end-to-end in production environments Strong Python skills with hands-on use of ML libraries like Scikit-learn, TensorFlow, PyTorch, or Hugging Face Solid understanding of machine learning fundamentals and performance evaluation techniques Experience working in cloud platforms ...

Fundamentals: You aren't limited to APIs. You have a background in training and evaluating models (TensorFlow/PyTorch/Keras/Scikit-learn) and know when a simple classifier is better than a generative model. Data Fluency: You understand how to build datasets from scratch (bootstrapping, crowdsourcing ...

multiple domains (NLP, vision, audio, time series, tabular data). Proficient in Python and relevant ML/data science libraries (e.g., pandas, numpy, scikit-learn, PyTorch, transformers). Experience with cloud-based model deployment (AWS) and ML engineering best practices. Excellent communication, problem-solving, and project delivery skills. ...

marketing, pricing, and promotional levers, and how they influence commercial performance. Solid Python skills for data manipulation, modelling, and visualisation (e.g., pandas, NumPy, scikit-learn). High proficiency with Microsoft Office, particularly Excel, PowerPoint, and Word. Exceptional attention to detail and a commitment to analytical rigour. Ability ...

Forecasting , Probabilistic Modelling , or Combinatorial Optimization . Technical Proficiency: Expert-level Python skills with deep experience in libraries such as PyTorch, TensorFlow, or Scikit-learn . Problem Solving: A track record of applying theoretical concepts to solve messy, real-world business problems. Communication: Ability to explain complex mathematical ...

Required Experience: Proven experience as an AI Engineer or Machine Learning Engineer Advanced Python skills with experience in ML frameworks (e.g. PyTorch, TensorFlow, scikit-learn) Strong understanding of machine learning algorithms and applied AI Experience deploying models into production environments Comfortable working in startup or fast-paced delivery ...

Data Scientist Hybrid Working – Local Site – 1-2 days a week on site. Financial Services Lorien's leading banking client is looking for a number of Data Scientists to join them on a new long ...

This is a unique opportunity to work at the cutting edge of AI, data technology, and elite football analytics. As a Data Scientist, you’ll join a collaborative, high-performing team with a culture rooted ...