Engaging with business & functional partners to understand business priorities, ask relevant questions, and scope same into an analytical solution document calling out how the application of data science will improve decision making- In-depth understanding of techniques to prepare the analytical data set leveraging multiple complex data set sources
Building Statistical models and ML algorithms with practitioner-level competency
Writing structured, modularized & computationally efficient production-ready codes using Continuous Improvement principles (development of knowledge assets and reusable modules on GitHub, Wiki, etc) with expert competency
Packaging the results in a manner that is easy to consume for the business (insight-led, visually easy to understand) and answering the original question)
Working with the line manager to ensure application/consumption and also think beyond the immediate ask and spot opportunities to address the bigger business questions (if any)
Keeping up-to-date with the latest in data science and retail analytics, actively taking part in knowledge sharing among colleagues
Requirements & Skills:
Education: University
Professional experience: 7 years+
Required English level: Advanced (C1)
6+ years experience in data science application in Retail or CPG
Functional experience: Marketing, Supply Chain, Customer, Merchandising, Operations, Finance or Digital
Other required skills: Microsoft Office, Applied Math: Applied Statistics, Design of Experiments, Regression, Decision Trees, Forecasting, Optimization algorithms, Clustering, NLP. Tech: SQL, Hadoop, Spark, Python, Tableau, MS Excel, MS Powerpoint, GitHub.
