Data Scientist - Associate - ML / Python

Associate Data Scientist – ML / Python - London/Hybrid Working

What you'll do

As a Data Scientist and member of our Data Science team, you will play a pivotal role in developing in-house data science solutions that automate decision-making and provide valuable insights across our business. Working in cross-functional agile squads, you will contribute to the design and development of our data science products. You will deliver high-quality analyses that guide future development work and contribute to the team's continuous learning and upskilling efforts.

Why join us

• Wide impact. Deploying models here means improving the experience of millions of customers each day.
• Range of projects. Our projects vary from supply chain optimisation for Argos, predicting which substitution products online shoppers prefer, to helping our Sainsburys colleagues keep shelves full.
• Focus on data science work. Access to extensive, clean, and well-documented data in our industry-leading platform: spend your time building data science solutions, not cleaning datasets.
• Time for growth. 10% of time set aside for learning & personal development
• Learning and mentoring. With a team of 50 data scientists, engineers and product managers, there are lots of opportunities to learn from colleagues through knowledge shares, pair programming, and communities of practice.
• Flexible working. Our team prioritizes hybrid working, both at home and in our central London Farringdon office.
• Save on groceries. 10% discount on products across Sainsburys (Up to 15% for two days each week!)

Join us and be part of a team that encourages innovation, values your expertise, and prioritises work-life balance while delivering exceptional results.

What you need to excel in this role: 

Essential:

• Educated to degree level, preferably within a mathematical, statistical or STEM discipline

• Proven track record of using Python and SQL to deliver complex ML solutions in a corporate environment or substantial relevant academic experience.

• Strong statistical foundation in concepts such as regression, hypothesis testing and experimental design.

• Strong presentation skills and business acumen: you regularly receive positive feedback about your ability to explain complex topics to non-technical audiences
• You feel comfortable working independently to achieve results using your own guidance and initiative.
• Experience getting the best out of sklearn and tree-based models. 

• Highly proficient in Git best practices.

• You are familiar with software engineering best practises and can utilise them to produce code that passes an engineering code review. 

Desirable:

• A relevant Post-graduate degree (Masters or PhD) within a mathematical, statistical or other STEM discipline.

• Experience delivering value on ML projects in retail (in areas such as price elasticity or differential pricing) or supply chain (demand forecasting, optimisation).
• Experience using ML with mathematical optimisation.
• Experience working with and applying causal inference.
• Experience working with and deploying Graphical Neural Networks [GNNs] in industry.

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