26 to 50 of 122 Statistics Jobs in London

improving data acquisition practices, automated data pipelines, data validation methods, and related data tasks Essential Skills & Experience: Bachelor's Degree in Business, Marketing, Economics, Statistics, Computer Science, or related analytical/technical field. Track record years of experience in marketing, data, STEM, or related quantitative disciplines. Ability to navigate across ...

clear link to downstream effect of spend.**Required Experience & Qualifications*** Bachelor's, Master’s, or PhD (preferably in field such as Computer Science, Mathematics, Statistics, Financial Engineering, or equivalent).* Significant professional experience (typically 7–12+ years) in relevant data roles, or related areas.* Demonstrated success working with technical teams ...

candidate will have experience in problem solving, data engineering, and stakeholder communication, with a background in a quantitative discipline (e.g. computer science, engineering, physics, statistics, or applied mathematics). The role involves working within cross-functional teams to address complex challenges and support decision-making across the sports industry, including ...

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 ...

high-quality code and provide prompt, effective support to resolve issues as they arise. Qualifications and Requirements: Degree educated in either Computer Science, Mathematics, Statistics, Financial Engineering, or a related quantitative field. Strong programming skills and advanced proficiency in Python. Strong understanding of probability theory and derivative option pricing. Experience ...

applicable to designing and improving large scale recommender systems, data engineering, and machine learning You have a Master’s or PhD in Computer Science, statistics, or an engineering field with 5+ years of experience Where will you be? London(Remote) What's in it for you? At ShareChat, our values ...

experience are out of scope for the pilot cohort. • A technical or quantitative undergraduate background is welcome: computer science, engineering, physics, applied mathematics, statistics, computational biology, industrial engineering, operations research, information systems, or quantitative economics. We will also consider non-technical majors with visible builder evidence such as a GitHub ...

excel as a Principal Data Scientist, you will typically possess:· Bachelor's/Master's degree in a quantitative field (e.g., Computer Science, Statistics, Mathematics, Physics, Engineering) or equivalent.· Extensive professional experience in data science, with a proven track record of technically leading and successfully delivering complex, impactful, and production … Large Language Models (LLMs), and related areas such as Natural Language Processing (NLP) or Computer Vision, relevant to business solutions.· Solid understanding of foundational statistics and experimental design.· Familiarity with or experience on cloud platformsImpact and Achievements:As a Principal Data Scientist, your success will be measured by your ability ...

data and processes are ready. During market – sporadically monitoring behaviour and performance of strategies. Qualifications Quantitative background - including Master/PhD’s in Mathematics, Statistics, Econometrics, Financial Engineering, Operations Research, Computer Science and Physics from a top University. Required Skills Programming proficiency with at least one major programming or scripting ...

processes are ready. During market - sporadically monitoring behaviour and performance of strategies. Ideal Candidate: Quantitative background - including Master/PhD's in Mathematics, Statistics, Econometrics, Financial Engineering, Operations Research, Computer Science and Physics from a top University. Programming proficiency with at least one major programming or scripting language (Python, C++ ...

tools. The Candidate Key attributes of a suitable AI Engineer or Senior AI Engineer include: Strong Data Science Foundations – bring solid grounding in statistics and machine learning, along with strong programming skills – Python preferred. Passion for Cutting-Edge AI – You actively experiment with and apply modern AI technologies such ...

graduate, with relevant course work, internship, or other applicable experience or knowledge Bachelor's degree in a quantitative or related field such as Mathematics, Statistics, Econometrics, Engineering, Operations Research, Computer Science, Physics, Economics, Finance Strong communication skills with the ability to collaborate with teammates globally Strong sense of urgency with ...

teams and external stakeholders on performance matters Support discussions relating to non-compliance and contractual performance Health & Safety Compile, analyse, and report health & safety statistics and exposure data Other Duties Carry out any additional reasonable tasks as requested to support the needs of the business Essential Skills & Experience Proven experience ...

Proven experience operating at senior practitioner level as a Machine Learning Engineer, AI Engineer, Applied ML Scientist, or equivalent Strong grounding in applied mathematics, statistics, and scientific practice Demonstrated ability to evaluate ML models using quantitative evidence and structured experimentation Excellent Python skills for building, evaluating, and iterating ...

Proven experience operating at senior practitioner level as a Machine Learning Engineer, AI Engineer, Applied ML Scientist, or equivalent Strong grounding in applied mathematics, statistics, and scientific practice Demonstrated ability to evaluate ML models using quantitative evidence and structured experimentation Excellent Python skills for building, evaluating, and iterating ...

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 ...