India / India / KA / Bangalore /

Data Science

#: 743999738672783 / 50245167

Mid-Senior Level


Job Description

About the Job

You will work with a Data Science team dedicated to the development of E-Commerce products, a new way to measure how people shop online. We are looking for someone to improve our E-Commerce offerings in India and then eventually work on other E-Commerce initiatives in Asian markets. 

You will serve as the key Data Science contact for Asian internal teams – in particular with: Client Service, Technology, Operations and Product Leadership. You will use your technical, mathematical and analytical skills to define and lead Global and regional innovation initiatives, methodology development,  KPI development & implementation, standards and best practices.  


  • Evaluate current E-Commerce Product methodologies to identify opportunities for enhancement

  • Deliver on methodology enhancements to E-Commerce products, improving overall quality from client perspective

  • Serve as Data Science’s chief point of contact for Asian eCommerce solutions. Present findings with stakeholders and support the resolution

  • Prototype as well as support pilot programs to drive innovation.  

A Little About You

Ideally, you should have knowledge of consumer panel behavior, experience with unmanaged panels and developing strategies for improving panel engagement, improving data quality, and influencing panelists. You should have a passion for consumer sourced data!


Critical/Must Haves:

  • Bachelor’s or Master’s Degree or Doctorate Degree with 3-5 years of experience in Consumer Insights/ Shopper Insights/ Data Analytics 

  • Experienced in high-level programming languages (Python or R)

  • Knowledge in SQL, working with queries and large-scale databases

  • Hands-on experience working with insights around consumer transaction data/ POS data/ Shopper panels / Panel and Data management

Other Qualifications:

  • Excellent statistical and logic skills. Experience in trend analysis, multivariate statistics (parametric/ non-parametric), sampling, bias reduction, indirect estimation, data aggregation techniques, data fusion, and model validation techniques

  • Experience implementing weighting and projection schema (e.g. RIM weighting) and clustering techniques (e.g. K-means, nearest-neighbour, random forests)

  • Strong communication and collaboration skills

  • Ability to effectively convey complex concepts to non-experts

  • Business acumen, the ability to link client's needs with the business

  • Ability to manage multiple projects simultaneously