1 to 25 of 68 Remote/Hybrid Statistics Jobs in London

innovations, and advocate for investments that deliver competitive advantage and risk reduction. Required Qualifications Education : Master’s or Ph.D. in Computer Science, Data Science, Statistics, Engineering, or a related quantitative field. Experience : 10+ years in data science, analytics, or related technology roles, with a minimum of 5 years in leadership ...

tools Version control proficiency (Git) all analytical work should be reproducible and code-reviewed Statistical & Analytical Foundation Postgraduate qualification (Master's or equivalent) in Statistics, Applied Mathematics, Machine Learning, Data Science, or a closely related quantitative field or demonstrated equivalent experience Deep understanding of statistical inference, uncertainty quantification ...

usability of analytical outputs Researching emerging data science trends and recommending improvements Here are the skills you'll need: Degree in Data Science, Statistics, Computer Science, Economics or related field Competence in Python, R or SQL for data manipulation and analysis Experience using data visualisation tools (Power BI, Tableau ...

stage projects Strong written and spoken English, with excellent communication skills Preferred Experience Advanced degree (Master’s or PhD) in Data Science, Computer Science, Statistics, Mathematics, or related field Experience with GenAI/LLMs and NLP applications Knowledge of regulatory frameworks in financial services (e.g., GDPR, model risk governance) Company ...

Strong SQL and Python experience Previously worked with large datasets. Strong Data modelling skills Data visualisation (Tableau or Power BI) Degree in Maths, Economics, Statistics, Finance or any quantitative subject Salary: Excellent + bonus + package Location: London (good work from home options available) If you are interested in this ...

Experience with Neo4j or other graph databases Experience with graph algorithms and network analysis Experience with Helm and Kubernetes operators Background in data science, statistics, or scientific computing Experience with graph analytics or network analysis Experience with RAG, LLM Orchestration and MCP Experience in early-stage startups What We Offer ...

Experience with Neo4j or other graph databases Experience with graph algorithms and network analysis Experience with Helm and Kubernetes operators Background in data science, statistics, or scientific computing Experience with graph analytics or network analysis Experience with Apple and Google App Stores Experience in early-stage startups What We Offer ...

your career within an AI-led organisation. What They’re Looking For Degree in a quantitative or technical field (e.g. Computer Science, AI, Mathematics, Statistics, Physics, Engineering) Strong Python skills with experience building machine learning models and scalable algorithms Proven experience working with large, complex datasets to optimise performance ...

turn insights into action.You’ll work within projects from data strategy sqand collection through to modelling, insight generation and activation, applying econometrics, regression, Bayesian statistics and machine learning to complex marketing and customer datasets.You’ll translate analytics into clear commercial recommendations, build dashboards and visual storytelling tools ...

domain driven architecture/operating model to drive the growth of your business domains. Qualifications: Bachelor’s degree in computer science, Data Science, Statistics, Mathematics, or a related field. Minimum of 8+ years of experience in data modeling in the property and casualty insurance industry. Proficiency in SQL, data modeling ...

experience: data pipelines, model development, deployment, and monitoring Strong Python and ML engineering skills (PyTorch or JAX) PhD in ML, Statistics, Computer Science, or related field (or equivalent research output) Ability to communicate complex ideas clearly to both technical and non-technical audiences Nice to Have Experience in asset management ...

such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded responsible and ethical AI principles from design through deployment. Integrate model driven insights into personalisation engines, tailoring ...

such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded responsible and ethical AI principles from design through deployment. Integrate model driven insights into personalisation engines, tailoring ...

such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded responsible and ethical AI principles from design through deployment. Integrate model driven insights into personalisation engines, tailoring ...

such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded responsible and ethical AI principles from design through deployment. Integrate model driven insights into personalisation engines, tailoring ...

such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded responsible and ethical AI principles from design through deployment. Integrate model driven insights into personalisation engines, tailoring ...

such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded responsible and ethical AI principles from design through deployment. Integrate model driven insights into personalisation engines, tailoring ...

such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded responsible and ethical AI principles from design through deployment. Integrate model driven insights into personalisation engines, tailoring ...

such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded responsible and ethical AI principles from design through deployment. Integrate model driven insights into personalisation engines, tailoring ...

such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded responsible and ethical AI principles from design through deployment. Integrate model driven insights into personalisation engines, tailoring ...

such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded responsible and ethical AI principles from design through deployment. Integrate model driven insights into personalisation engines, tailoring ...

such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded responsible and ethical AI principles from design through deployment. Integrate model driven insights into personalisation engines, tailoring ...

such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded responsible and ethical AI principles from design through deployment. Integrate model driven insights into personalisation engines, tailoring ...

such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded responsible and ethical AI principles from design through deployment. Integrate model driven insights into personalisation engines, tailoring ...

such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded responsible and ethical AI principles from design through deployment. Integrate model driven insights into personalisation engines, tailoring ...