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+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.