- Drive the full lifecycle of Data Science projects: from gathering and understanding the end-user needs to implement a fully automated solution.
- Develop and provision of Data pipelines to enable self-service reports and dashboards.
- Deploy Machine learning techniques to answer the appropriate business problems using R or Python.
- Visualize data using Tableau and create repeatable visual analysis for end users to use as tools.
- Take ownership of the existing BI platforms and maintain the data integrity and accuracy of the numbers and data sources.
- Know Agile - Scrum project management experience/knowledge - Ability to prioritise, pushback and effectively manage a data product and sprint backlog.
- 6-8+ years of professional data science or product analytics experience focussed on empirical analytics, data mining, and predictive analytics to develop measurable insights.
- Strong proficiency in writing production-quality code preferable in R/Python, engineering experience with machine learning projects like time series forecasting, Classification and optimization problems.
- Experience with Tableau, Power BI, Superset or any standard data visualization tools.
- Experience in building data pipelines using MPP databases (e.g. Redshift, BigQuery) and Google Analytics/Google Tag Manager is a bonus.
- Management experience would be an added advantage point.
- Exhibits sound business judgment, a proven ability to influence others, strong analytical skills, and a proven track record of taking ownership, leading data-driven analyses, and influencing results
E-commerce / logistics / fashion retail background a bonus.