s degree in a STEM field: Statistics, Mathematics, Computer Science, Engineering, or similar. Programming proficiency: Strong experience with Python and SQL; familiarity with libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch. Machine learning expertise: Hands-on experience in supervised and unsupervised learning, with exposure to NLP, computer vision, or deep learning a plus. Data visualisation: Proficiency More ❯
South West London, London, United Kingdom Hybrid / WFH Options
Serve Legal
and iteration. Data Storyteller makes technical findings accessible and impactful. Connector collaborates seamlessly across data, commercial, and ops teams. Hard Skills Required Programming & Data Science: Python (Pandas, NumPy, scikit-learn, TensorFlow or PyTorch) essential; R (desirable) Data Engineering & Cloud: Advanced SQL, ETL/ELT tools (Airflow/dbt), AWS/Azure/GCP Machine Learning & AI: Classification, regression More ❯
and iteration. Data Storyteller makes technical findings accessible and impactful. Connector collaborates seamlessly across data, commercial, and ops teams. Hard Skills Required Programming & Data Science: Python (Pandas, NumPy, scikit-learn, TensorFlow or PyTorch) essential; R (desirable) Data Engineering & Cloud: Advanced SQL, ETL/ELT tools (Airflow/dbt), AWS/Azure/GCP Machine Learning & AI: Classification, regression More ❯
in applying statistical and machine learning techniques to unstructured data, particularly with image and geometric datasets. Proficiency with data science and machine learning libraries in Python (Pandas, NumPy, Scikit-learn, PyTorch, or TensorFlow). Demonstrable experience developing and deploying complex front-end applications using the React ecosystem. Proficiency in designing, implementing, and optimising GraphQL APIs for thin-client More ❯
in applying statistical and machine learning techniques to unstructured data, particularly with image and geometric datasets. Proficiency with data science and machine learning libraries in Python (Pandas, NumPy, Scikit-learn, PyTorch, or TensorFlow). Demonstrable experience developing and deploying complex front-end applications using the React ecosystem. Proficiency in designing, implementing, and optimising GraphQL APIs for thin-client More ❯
in applying statistical and machine learning techniques to unstructured data, particularly with image and geometric datasets. Proficiency with data science and machine learning libraries in Python (Pandas, NumPy, Scikit-learn, PyTorch, or TensorFlow). Demonstrable experience developing and deploying complex front-end applications using the React ecosystem. Proficiency in designing, implementing, and optimising GraphQL APIs for thin-client More ❯
concepts clearly to technical and non-technical stakeholders. Essential Skills & Experience Hands-on experience in ML, NLP, and GenAI (LLM/SLM). Proficiency in Python (Pandas, NumPy, Scikit-learn, PyTorch/TensorFlow). Experience with SQL/NoSQL databases, APIs, and data integration. Exposure to on-premise/open-source AI frameworks. Strong problem-solving and communication More ❯
concepts clearly to technical and non-technical stakeholders. Essential Skills & Experience Hands-on experience in ML, NLP, and GenAI (LLM/SLM). Proficiency in Python (Pandas, NumPy, Scikit-learn, PyTorch/TensorFlow). Experience with SQL/NoSQL databases, APIs, and data integration. Exposure to on-premise/open-source AI frameworks. Strong problem-solving and communication More ❯
London, South East, England, United Kingdom Hybrid / WFH Options
Method Resourcing
at scale. Deep familiarity with core ML concepts (classification, time-series, statistical modeling) and their real-world tradeoffs. Fluency in Python and commonly used ML libraries (e.g. pandas, scikit-learn; experience with PyTorch or TensorFlow is a plus). Experience with model lifecycle management (MLOps), including monitoring, retraining, and model versioning. Ability to work across data infrastructure, from More ❯
Qualifications Experience Extensive experience in data science, machine learning, or advanced analytics, ideally in a technical leadership role Proven expertise in Python and ML frameworks (e.g., PyTorch, TensorFlow, Scikit-learn) and experience across NLP, computer vision, and LLMs Strong statistical foundation, including A/B testing, causal inference, and experimental design Proficiency in SQL and working with large More ❯
TensorFlow and PyTorch. Programming: Solid experience in Python and SQL. Experience with R is a nice-to-have. ML and AI: Practical experience using ML modeling libraries like Scikit-Learn, Keras, TensorFlow, PyTorch and similar Generative AI: Some hands-on experience with LLMs for prompt engineering or agents is preferred Cloud Expertise: Building, deploying and monitoring models on More ❯
AI Solutions Engineer x 2 AI Solutions, B2B, B2C, Azure, AI Foundry, Open-AI, Microsoft Copilot Studio, Machine Learning, Python, TensorFlow, PyTorch, scikit-learn, Large Language Models, LLM, Data preprocessing, REST API, Microservices architecture, MLOps, CI/CD for ML, Power-BI, Docker, Kubernetes, AI Ethics, Cloud Platforms, AWS, Google Cloud Platform, SQL, NoSQL, DevOps, Financial services, Regulatory More ❯
Essential Experience: Hands-on experience using machine learning frameworks (e.g., Scikit-learn, TensorFlow, PyTorch) to design and implement solutions.Experience deploying AI/ML models to production systems in collaboration with engineering teams. Basic experience with cloud technologies (e.g., AWS, Azure, or GCP). Experience creating interactive visualizations and dashboards using tools such as Power BI or Tableau to More ❯
Experience: Proven ability to solve complex, real-world problems through data science and analytics. Experience coaching and reviewing work of junior team members. Strong Python skills (pandas, numpy, scikit-learn) and a solid grounding in probability and statistics. Deep knowledge of machine learning methods and their practical application. Experience managing multiple end-to-end data science projects across More ❯
Reigate, Surrey, England, United Kingdom Hybrid / WFH Options
esure Group
them to strong results. Experienced in engaging with non-technical partners to scope, design and build an appropriate ML solution. Proficient with Python data science stack, e.g., pandas, scikit-learn, Jupyter etc., and version control, e.g., Git. Knowledge of OO programming, software design, i.e., SOLID principles, and testing practices. Knowledge and working experience of AGILE methodologies. Proficient with More ❯
Reigate, Surrey, England, United Kingdom Hybrid / WFH Options
esure Group
them to strong results. Experienced in engaging with non-technical stakeholders to scope, design and build an appropriate ML solution. Proficient with Python data science stack, e.g., pandas, scikit-learn, Jupyter etc., and version control, e.g., Git. Exposure to LLMOps, model monitoring principles, CI/CD and associated tech, e.g., Docker, MLflow, k8s, FastAPI etc. Knowledge of Langchain More ❯
sponsorship*** Key Responsibilities: Research and deploy LLM-based solutions (e.g., LangChain, Mastra.ai, Pydantic) for document processing, summarization, and clinical Q&A systems. Develop and optimize predictive models using scikit-learn, PyTorch, TensorFlow, and XGBoost. Design robust data pipelines using tools like Spark and Kafka for real-time and batch processing. Manage ML lifecycle with tools such as Databricks More ❯
What We’re Looking For 2–5 years of experience in ML Engineering or MLOps. Strong proficiency in Python and experience with ML libraries/frameworks (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch). Hands-on experience implementing end-to-end ML pipelines (data ingestion, training, validation, serving). Familiarity with ML workflow orchestration tools (Airflow, Prefect, Kubeflow) and More ❯
What We’re Looking For 2–5 years of experience in ML Engineering or MLOps. Strong proficiency in Python and experience with ML libraries/frameworks (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch). Hands-on experience implementing end-to-end ML pipelines (data ingestion, training, validation, serving). Familiarity with ML workflow orchestration tools (Airflow, Prefect, Kubeflow) and More ❯
systems in production. What We’re Looking For 3+ years of experience in Data Science. Strong proficiency in Python and experience with ML libraries/frameworks (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch). Hands-on experience implementing end-to-end ML pipelines (data ingestion, training, validation, serving). Familiarity with ML workflow orchestration tools (Airflow, Prefect, Kubeflow) and More ❯
systems in production. What We’re Looking For 3+ years of experience in Data Science. Strong proficiency in Python and experience with ML libraries/frameworks (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch). Hands-on experience implementing end-to-end ML pipelines (data ingestion, training, validation, serving). Familiarity with ML workflow orchestration tools (Airflow, Prefect, Kubeflow) and More ❯
sponsorship*** Key Responsibilities: Research and deploy LLM-based solutions (e.g., LangChain, Mastra.ai, Pydantic) for document processing, summarization, and clinical Q&A systems. Develop and optimize predictive models using scikit-learn, PyTorch, TensorFlow, and XGBoost. Design robust data pipelines using tools like Spark and Kafka for real-time and batch processing. Manage ML lifecycle with tools such as Databricks More ❯
What We’re Looking For 2–5 years of experience in ML Engineering or MLOps. Strong proficiency in Python and experience with ML libraries/frameworks (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch). Hands-on experience implementing end-to-end ML pipelines (data ingestion, training, validation, serving). Familiarity with ML workflow orchestration tools (Airflow, Prefect, Kubeflow) and More ❯
What We’re Looking For 2–5 years of experience in ML Engineering or MLOps. Strong proficiency in Python and experience with ML libraries/frameworks (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch). Hands-on experience implementing end-to-end ML pipelines (data ingestion, training, validation, serving). Familiarity with ML workflow orchestration tools (Airflow, Prefect, Kubeflow) and More ❯
