Data Scientist

• Job Term (e.g. FTC/Perm): Permanent
• Job: Location: London

Why Join Us

We have ~90 Analysts and Data Scientists within Customer & Loyalty Analytics focusing on a wide range of business questions, and we have millions of known customers to play with.

This team is focussed on building our personalised customer decisioning engine, known internally as Krang. We are the brain behind an optimised selection of offers, mechanics and discounts used to drive desired customer behaviour. We do some of Sainsbury’s most complex modelling, forecasting, tool building, and insights-generation and use agile working methodologies to make sure we’re prioritising the right outcomes. Our Data Scientists are critical in supporting Sainsbury’s to be successful in our corporate strategy of Connecting to our Customers.

What You’ll Do

Specifically, this Data Scientist role will be supporting the team in the following:  

• Understanding known behaviour and trends across Sainsbury’s.
• Actively contributing towards ongoing optimisation of our personalisation capabilities, aiming to choose the right message for a particular customer, at the right time, through the right channel and with the right value.
• Understanding how customers see value and the profitability of an individual’s relationship and sensitivity with price, promotions, Nectar points and offers in order to consider our levers for growth.
• Identifying new approaches and methodologies to develop how we do things.
• Being the first port of call when it comes to leveraging our Group-wide dataset.
• Ensuring every piece of code and output we deliver is documented, repeatable, scalable and sharable via appropriate, collaborative tools (e.g. Git, Confluence).
• Being an active, participating member of the wider Data & Analytics community at Sainsbury’s.
• Pairing with Data Engineers to productionise our outputs.

What I Need To Know

• Extensive programming ability across Python and strong ability to use SQL, with a proven experience of analysing data in a corporate environment.
• Strong Data Science skills and statistical foundation in concepts such as predictive modelling, causal inference, clustering and linear optimisation.
• Experience using Jupyter notebooks and version control within a team using Git.
• Experience using cloud platforms such as AWS or Azure and associated ML tools is desirable but not essential.
• A curious problem solver who is proactive at developing their technical skills.
• Business acumen and commercial awareness
• Ability to articulate required outcomes and present analytics work succinctly.
• Independence to achieve results and work under own guidance and initiative
• Able to have effective technical conversations with data engineers.
• Curiosity, scepticism and attention to detail regarding data quality, samples, bias and ethics.
• An awareness and understanding of technology trends and direction in Data Science, AI and analytics.

Essential Criteria

• Extensive programming ability across Python and strong ability to use SQL, with a proven experience of analysing data in a corporate environment.
• Strong Data Science skills and statistical foundation in concepts such as predictive modelling, causal inference, clustering and linear optimisation.
• Experience using Jupyter notebooks and version control within a team using Git.
• Experience using cloud platforms such as AWS or Azure
• Ability to articulate required outcomes and present analytics work succinctly.