Data Modeler

Experis
London
11 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Modeler — AWS Data Warehouse Migration (Remote)

Sustainability Data Scientist & Impact Modeler

Quantitative Derivatives Modeler

Statistician / Data Modeller

Statistician / Data Modeller

Head of Data Architecture

Location: London Job Type: Contract Industry: Enterprise Applications Job reference: BBBH394538_1737996139 Posted: about 4 hours ago

Role: Data Modeler

Location: UK Remote

Duration: 6 Months

Day rate: £410 inside IR35

Required Skills:

Experience in data architecture and modelling. Strong understanding of relational and non-relational database systems. Proficiency in data modelling tools (Erwin, SAP Power Designer). Experience with data governance and data quality practices. Understanding of cloud platforms, particularly Azure. Knowledge of data integration and ETL processes. Familiarity with data warehousing, data marts, and data lakes. Exposure to healthcare industry standards, such as FHIR, is a plus. Excellent analytical and problem-solving skills. Strong communication and collaboration abilities. Ability to work independently and as part of a team. Data Modelling: Design and implement conceptual, logical, and physical data models. Define the structure of databases, including tables, relationships, and constraints

Nice to have skills:

Data Storage and Integration: Select appropriate data storage technologies, including SQL and NoSQL databases. Design and implement data integration strategies to ensure seamless data flow. Optimise data processing and query performance. Data Governance: Develop and enforce data policies and standards to maintain data quality and consistency. Implement security measures to protect data confidentiality, integrity, and availability. Create and manage data dictionaries to document data definitions and usage. Data Product Development: Conceptualise and design data products to meet business needs. Collaborate with business analysts and end users to understand requirements and translate them into technical solutions.

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Education Jobs

Maths for Data Science Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are applying for data science jobs in the UK, the maths can feel like a moving target. Job descriptions say “strong statistical knowledge” or “solid ML fundamentals” but they rarely tell you which topics you will actually use day to day. Here’s the truth: most UK data science roles do not require advanced pure maths. What they do require is confidence with a tight set of practical topics that come up repeatedly in modelling, experimentation, forecasting, evaluation, stakeholder comms & decision-making. This guide focuses on the only maths most data scientists keep using: Statistics for decision making (confidence intervals, hypothesis tests, power, uncertainty) Probability for real-world data (base rates, noise, sampling, Bayesian intuition) Linear algebra essentials (vectors, matrices, projections, PCA intuition) Calculus & gradients (enough to understand optimisation & backprop) Optimisation & model evaluation (loss functions, cross-validation, metrics, thresholds) You’ll also get a 6-week plan, portfolio projects & a resources section you can follow without getting pulled into unnecessary theory.

Jobs

Neurodiversity in Data Science Careers: Turning Different Thinking into a Superpower

Data science is all about turning messy, real-world information into decisions, products & insights. It sits at the crossroads of maths, coding, business & communication – which means it needs people who see patterns, ask unusual questions & challenge assumptions. That makes data science a natural fit for many neurodivergent people, including those with ADHD, autism & dyslexia. If you’re neurodivergent & thinking about a data science career, you might have heard comments like “you’re too distracted for complex analysis”, “too literal for stakeholder work” or “too disorganised for large projects”. In reality, the same traits that can make traditional environments difficult often line up beautifully with data science work. This guide is written for data science job seekers in the UK. We’ll explore: What neurodiversity means in a data science context How ADHD, autism & dyslexia strengths map to common data science roles Practical workplace adjustments you can request under UK law How to talk about your neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in data science – & how to turn “different thinking” into a real career advantage.

Jobs

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.