Data Scientist

Hertford
2 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist (Globally Renowned Retail Group)

Data Scientist / Data Analyst

We are seeking a talented and hands-on Data Scientist / Data Analyst to join our team. In this role, you will be instrumental in modernising how we handle and analyse our business data. You'll bridge the gap between our legacy on-premises systems and a modern cloud-based data architecture, enabling real-time, data-driven decision-making across the organisation. The ideal candidate will also have strong experience with large language models (LLMs) and machine learning (ML), which are central to the analytical capabilities we are building. This role includes deploying agentic workflows to automate and enhance decision-making processes.

Key Responsibilities:

  • Legacy System Integration: Work with existing SQL-based backend systems (e.g., Redbook 10, Sage 200, Sage CRM) running on virtualized infrastructure in a private cloud. Design and implement lightweight coding solutions to integrate and transfer data from these legacy systems into cloud-based data lakes or warehouses.

  • Cloud Data Solutions and Visualization: Migrate and organize data within platforms like Microsoft Fabric. Develop and maintain Power BI dashboards to provide real-time insights and analytics, helping the senior leadership team and other stakeholders make informed decisions.

  • Technical and Analytical Expertise: Use your coding and data analysis skills to streamline data flows and improve efficiency. Bring at least 2–3 years of real-world experience in a similar environment, along with a relevant university-level qualification.

    Skills and Experience Required:

  • Proven experience with SQL-based systems in a virtualized private cloud.

  • Ability to build lightweight integrations and interfaces to move data from legacy systems to modern cloud data solutions.

  • Hands-on experience with data visualization tools such as Power BI.

  • Strong analytical and problem-solving skills, and the ability to translate business requirements into actionable data insights.

  • Experience with large language models (LLMs) and machine learning (ML) is an advantage as well as practical experience in deploying agentic workflows for automated, intelligent data processing and analysis

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.

How to Write a Data Science Job Ad That Attracts the Right People

Data science plays a critical role in how organisations across the UK make decisions, build products and gain competitive advantage. From forecasting and personalisation to risk modelling and experimentation, data scientists help translate data into insight and action. Yet many employers struggle to attract the right data science candidates. Job adverts often generate high volumes of applications, but few applicants have the mix of analytical skill, business understanding and communication ability the role actually requires. At the same time, experienced data scientists skip over adverts that feel vague, inflated or misaligned with real data science work. In most cases, the issue is not a lack of talent — it is the quality and clarity of the job advert. Data scientists are analytical, sceptical of hype and highly selective. A poorly written job ad signals unclear expectations and immature data practices. A well-written one signals credibility, focus and serious intent. This guide explains how to write a data science job ad that attracts the right people, improves applicant quality and positions your organisation as a strong data employer.

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.

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.