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Data Scientist - Hybrid Working - London/Home
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 one of the largest logistics networks in the country, predicting which substitution products online shoppers prefer, to helping our instore 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!)
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What you need to excel in this role:
Essential Criteria
- Educated to degree level, preferably within a mathematical, statistical or STEM discipline.
- A solid track record of individually contributing to value-driving data science projects in a commercial setting.
- You have experience of writing production grade code using Python and SQL, as some of our systems involve real-time inference that affect millions of customer transactions.
- Strong presentation skills and business acumen, you regularly receive positive feedback about your ability to explain complex topics to non-technical audiences.
- You can feel comfortable working independently to achieve results using your own guidance and initiative.
- Strong statistical foundation in concepts such as regression, hypothesis testing, experimental design.
- Experience getting the best out of sklearn and tree-based models.
- Highly proficient in Git best practices.
- Experience working in cloud environments (Azure, AWS, GCP,).
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Desirable
- A relevant Post-graduate degree (Masters or PhD) within a mathematical, statistical or other STEM discipline.
- Experience building or maintaining machine learning pipelines and endpoints in Azure ML.
- Experience delivering value on ML projects in retail (in areas such as price elasticity or differential pricing) or supply chain (demand forecasting, optimisation etc.).
- Experience going from unstructured business problems through to well defined Data science solutions
- Our products often utilize mathematical optimisation, so experience in this area is highly desirable.
- Experience in applying causal frameworks to data science solutions and applying causal inference methods.
- Experience working with and deploying Graphical Neural Networks [GNNs] in industry.
- Experience with other more complex models and frameworks.
- Experience working within in a cross functional team.
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