Join Gopuff as an Inventory Management Data Scientist, where together with our 'In-Stock Development Lead Data Analyst', you will support our product development, decision making and analysis on product ordering, inventory management and how we balance exceptional customer experience against profitability.
In this role, you will contribute to the rapid growth of our business by building decision support systems, together with analysing and sharing insight on our huge datasets to optimise our category performance.
You will have the opportunity to develop innovative approaches and solutions to the complex problems that we need to solve and will work alongside a talented UK Data Team and wider Gopuff Data Community to support your ongoing development. We recognise that people come from diverse backgrounds and skills and welcome all to apply.
You Will:
1. In collaboration with Category and In-Stock Management teams, work on our Stock Ordering Tool and Compliance Improvements (infrastructure development and buying policies).
2. In collaboration with the wider Data Team and Community, work on measuring and reporting availability levels and their influence on revenue and order volume within Gopuff.
3. Provide clear insight into the value and success of different buying policies we have built into our Stock Ordering Tool to ensure we are hitting the target levels of Expirations and Availability.
4. Set dynamic targets for Availability and Expirations for each Subcategory.
5. Design and measure experiments in Stock Ordering Tool buying policies.
6. Perform deep dives and post-implementation reviews to analyse problems, identify opportunities and suggest experiments for the future within the scope of Availability and Expirations Reporting.
You Have:
1. Bachelor's Degree in Business, Mathematics, Statistics, Data Science or other quantitative discipline.
2. 2+ years of experience in analytics or data science - preferably in fields related to grocery, operations, marketing or consumer products.
3. Strong experience in SQL and databases, with an ability to write structured and efficient queries on large data sets.
4. Proficiency with dbt, Python or R is a strong plus.
5. Experience with Supply Chain Analytics is a strong plus.
6. Development experience with BI platforms such as Looker, Tableau, Power BI.
7. An understanding of statistical analysis and experiment design.
Benefits:
1. Company RSU's (Company Shares)
2. Private Medical + Dental cover
3. Annual performance appraisal and bonus
4. Employee Discount + FAM membership
5. Career growth opportunities
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