Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Data Scientist – Finance BI

Sainsbury's
City of London
1 day ago
Create job alert

Please note, this role is based out of our London Store Support Centre & Home. Colleagues go into the office 1-2 days per week on average.


Why join us

Joining the Finance BI Analytics team at Sainsbury’s means working with one of the most exciting and rich retail data sets in the UK. You’ll play a pivotal role in driving commercial finance value through advanced analytics, statistical modelling, and data storytelling. In a dynamic and collaborative environment, you’ll support data-driven decisions across the business. We’re committed to continuous learning and development, so you’ll have plenty of opportunities to grow your technical and leadership skills while making a real difference.


What you’ll do

As a Data Scientist in the Finance BI team, you’ll play a key role in unlocking value from complex financial data, partnering closely with Finance Managers and senior stakeholders to deliver advanced analytical projects from end to end. You’ll apply statistical techniques such as regression analysis, time series modelling, and hypothesis testing to uncover trends, forecast outcomes, and solve business challenges. Your insights will drive strategic decisions, and you’ll be responsible for translating complex analytics into clear, compelling narratives that resonate with both technical and non-technical audiences. In addition, you’ll also support and mentor colleagues in the use of SQL, Python, and BI tools, helping to build strong analytical capability across the function.


Who you are

You’re a curious and driven data professional with a strong foundation in statistics and modelling. You enjoy solving complex problems and translating data into meaningful insights to both technical and non-technical stakeholders. You’re confident working with stakeholders at all levels up to director-level and thrive in a collaborative environment.


Essential Criteria

  • Educational degree in Mathematics, Statistics, Data Science, or a related analytical field is desirable
  • Experience applying statistical techniques and modelling in a commercial setting (such as regression analysis, time series forecasting and hypothesis testing).
  • Exposure to machine learning methods, including supervised and unsupervised learning, and model evaluation
  • Experience in SQL and Python for advance analytics and modelling (experience with Snowflake, R, GitHub, and Jira is a plus)
  • Experience using Python libraries such as pandas, scikit-learn, and statsmodels (or R equivalent)
  • Experience using BI tools like Power BI or Tableau to communicate insights
  • Experience mentoring or upskilling colleagues in analytics tools (such as SQL and BI Tools) and techniques

#LI-CE1


Qualifications

We are committed to being a truly inclusive retailer so you’ll be welcomed whoever you are and wherever you work. Around here, there’s always the chance to try something new — whether that’s as part of an evolving team or somewhere else across the business - and we take development seriously and promise to support you. We also recognise and celebrate colleagues when they go the extra mile and, where possible, offer flexible working. When you join our team, we’ll also offer you an amazing range of benefits. Here are some of them:


Starting off with colleague discount, you'll be able to save 10% on your shopping online and instore at Sainsbury's, Argos, TU and Habitat, and we regularly increase the discount to 15% at points during the year. We've also got you covered for your future with our pensions scheme and life cover. You'll also be able to share in our success as you may be eligible for a performance-related bonus of up to 10% of salary, depending on how we perform.


Your wellbeing is important to us too. You'll receive an annual holiday allowance and you can buy up to an additional week's holiday. We also offer other benefits that will help your money go further such as season ticket loans, cycle to work scheme, health cash plans, salary advance (where you can access some of your pay before pay day) as well access to a great range of discounts from hundreds of other retailers. And if you ever need it there is also an employee assistance programme.


Moments that matter are as important to us as they are to you which is why we give up to 26 weeks’ pay for maternity or adoption leave and up to 4 weeks’ pay for paternity leave.


Please see www.sainsburys.jobs for a range of our benefits (note, length of service and eligibiity criteria may apply).


Responsibilities

We’d all like amazing work to do, and real work-life balance. That’s waiting for you at Sainsbury’s. For a FTSE business, we move incredibly fast. When we’re not handling projects, we’re helping all corners of the wider group with what they’re trying to achieve. And around here, you can see the results of your work as soon as you walk into a store, which gives you a real sense of purpose and responsibility. Better still, the team around you will listen to your ideas and opinions, and you’ll have every chance to try something new. The sheer scale and complexity of our set-up means there’s always something else around the corner, and we’ll help and support you every step of the way. We’re trusted to get on with it. So get ready to make things happen here.


#J-18808-Ljbffr

Related Jobs

View all jobs

Commercial Data Analyst / Scientist

Commercial Data Analyst / Scientist

EMEIA Sales Finance - Data Scientist

NLP Data Scientist

Data Scientist / Analyst

Data Scientist / Analyst

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.

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

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.