14 of 14 Permanent Statistics Jobs in the West Midlands

operational research, big data and dashboarding deliveries Present findings to non-technical stakeholders Candidate Profile Active DV clearance (essential) Degree/Master's/PhD in Data Science, Mathematics, Statistics, Physics, Operational Research or similar Strong experience in advanced analytics, modelling, or operational research Skilled in Python, SQL and Excel Experience within the Defence & Security sector Ability to formulate problems More ❯

their development. Requirements 3-5 years of experience in data analytics, preferably in a consulting or advisory context. University degree 2.1 or higher (or equivalent) in Computer Science, Mathematics, Statistics, or a related field. Strong analytical and problem-solving skills, with a keen attention to detail. Proficiency in BI tools such as Power BI, Qlik, or Tableau. Solid understanding of More ❯

space (preferably in a consulting context) with at least 2 years at a senior leadership level University degree 2.1 or higher (or equivalent) in Computer Science/Mathematics/Statistics or equivalent. Proven track record in winning and delivering large, complex, data-led engagements. Demonstrable ability to own client relationships, originate work, and grow revenue. Deep understanding of the full More ❯

For Strong hands-on capability with SQL for analytics (complex queries, joins, CTEs, window functions). Solid experience using Python for data analysis and modelling. A strong mathematics or statistics background - essential for building robust analytical approaches. Experience working within, or closely with, a pricing, commercial, or revenue function . Ability to interpret data and communicate insights to non-technical More ❯

in Metabase that support operational planning. Collaborative mindset: Works well across Commercial, Supply, and Pricing functions. Education & Experience: You have a degree in a quantitative field such as Mathematics, Statistics, Economics, or Engineering, and 2–3 years of experience in analytics—preferably with exposure to commercial operations, pricing, or inventory analytics. Benefits Technology Incentive Scheme - we offer different bonus schemes More ❯

responsible for the collection and analysis of data from various sources in order to provide insights and solutions for various business problems using various tools and techniques, such as statistics, programming, databases, visualisation and machine learning. We're looking for someone with: Proven analytics skills, including mining, evaluation, and visualisation Technical writing experience in relevant areas, including queries, reports, and More ❯

ensure they understand the analyses and to provide explanation and interpretation for any areas of uncertainty. Providing expert advice and support to staff on the use of information and statistics made available to them and to communicate highly complex statistical/analytical information to non-statistical/analytical staff in a user-friendly manner. To provide specialist support with the More ❯

Dimensional Tensor Networks (Must have) Theoretical physics and statistical physics Dynamic systems (energy landscapes, emergent behaviours) Modelling and simulation Mathematics: Advanced linear algebra, optimisation, numerical methods Information theory Probability, statistics Graph theory Highly Valued: Machine Learning Experience: Specifically in parameter-free learning approaches, Bayesian methods and belief networks, reinforcement learning and graph neural networks, computational optimisation at scale, algorithms and More ❯

Dimensional Tensor Networks (Must have) Theoretical physics and statistical physics Dynamic systems (energy landscapes, emergent behaviours) Modelling and simulation Mathematics: Advanced linear algebra, optimisation, numerical methods Information theory Probability, statistics Graph theory Highly Valued: Machine Learning Experience: Specifically in parameter-free learning approaches, Bayesian methods and belief networks, reinforcement learning and graph neural networks, computational optimisation at scale, algorithms and More ❯

Dimensional Tensor Networks (Must have) Theoretical physics and statistical physics Dynamic systems (energy landscapes, emergent behaviours) Modelling and simulation Mathematics: Advanced linear algebra, optimisation, numerical methods Information theory Probability, statistics Graph theory Highly Valued: Machine Learning Experience: Specifically in parameter-free learning approaches, Bayesian methods and belief networks, reinforcement learning and graph neural networks, computational optimisation at scale, algorithms and More ❯

Dimensional Tensor Networks (Must have) Theoretical physics and statistical physics Dynamic systems (energy landscapes, emergent behaviours) Modelling and simulation Mathematics: Advanced linear algebra, optimisation, numerical methods Information theory Probability, statistics Graph theory Highly Valued: Machine Learning Experience: Specifically in parameter-free learning approaches, Bayesian methods and belief networks, reinforcement learning and graph neural networks, computational optimisation at scale, algorithms and More ❯

Dimensional Tensor Networks (Must have) Theoretical physics and statistical physics Dynamic systems (energy landscapes, emergent behaviours) Modelling and simulation Mathematics: Advanced linear algebra, optimisation, numerical methods Information theory Probability, statistics Graph theory Highly Valued: Machine Learning Experience: Specifically in parameter-free learning approaches, Bayesian methods and belief networks, reinforcement learning and graph neural networks, computational optimisation at scale, algorithms and More ❯

Dimensional Tensor Networks (Must have) Theoretical physics and statistical physics Dynamic systems (energy landscapes, emergent behaviours) Modelling and simulation Mathematics: Advanced linear algebra, optimisation, numerical methods Information theory Probability, statistics Graph theory Highly Valued: Machine Learning Experience: Specifically in parameter-free learning approaches, Bayesian methods and belief networks, reinforcement learning and graph neural networks, computational optimisation at scale, algorithms and More ❯

Dimensional Tensor Networks (Must have) Theoretical physics and statistical physics Dynamic systems (energy landscapes, emergent behaviours) Modelling and simulation Mathematics: Advanced linear algebra, optimisation, numerical methods Information theory Probability, statistics Graph theory Highly Valued: Machine Learning Experience: Specifically in parameter-free learning approaches, Bayesian methods and belief networks, reinforcement learning and graph neural networks, computational optimisation at scale, algorithms and More ❯