Senior Data Scientist - Consumer Goods/FMCG/Retail/eCommerce Domain

MANDATORY SKILLS:

5 years experience in a relevant Data Scientist role

Prior experience in Revenue Management/ Pricing/Media/ Social Media

Consumer goods FMCG/retail industry/ e-commerce domain experience is a MUST

Programming skills in Machine learning, NLP, Statistical Modelling, SAS, R, SQL and Python (as needed)

Extensive experience solving business problems using quantitative approaches.

Comfort with extracting, manipulating and analyzing complex, high volume, high dimensionality data from varying sources

Proficient in analytic tools like SAS, SPSS and R

TECHNICAL COMPETENCIES :

Proficient in Advanced MS Excel (Pivots, calculated fields, Conditional formatting, charts, dropdown lists etc.), MS PowerPoint and MS Access

Familiarity with relational databases RDBMS and intermediate level knowledge of SQL, and VBA coding, Excel Macros etc

Experience working with large data sets

The ideal candidate needs to be technically strong and be able to speak and articulate his point of view as he/she will be working very closely with global stakeholders.g on extremely challenging and complex projects. You might have the opportunity to travel and work from various geographies globally.

Behavioral Competencies :

Ability to manage conformity to established procedures & processes

Comfortable in handling large volume of data

Ability to work under pressure and have flexible working hours.

Excellent communication skills

Excellent in driving strong relationships with stakeholders

Highly results focused

Strong passion for data driven research for answering hard questions with data. Flexible analytic approach that allows for results at varying levels of precision.

Ability to communicate complex quantitative analysis in a clear, precise, and actionable manner.

Timeline Definition for Ad-hoc Requests

Responsible for Time Estimation (for completion of request) and Timeline Definition for every approved Request

Responsible for Execution of Ad-hoc Requests (including data extraction and preparation)

Resolve by self or escalate to the Revenue Management Analytics Lead, any issues which may arise to ensure minimum TAT (turn around time)

Present data and reports in an easy to - read and comprehend- manner

Proactively get reports/analysis validated by the Revenue Management Analytics Lead or Zone Director Analytics (if required) and incorporate feedback provided

Responsible for sharing of reports/analysis/updated models with the request generator

Responsibilities :

Suggested new products in to market and finding out the best combination of products line to maximizing the reach of consumers and market-share by analysis and to fix the price of the products

Conducted consumer research, in-market studies and retail landscape evaluation to develop predictive models as part of a concentrated effort to improve customer reach and product placement.

Create a model incorporating social media data into customer analytics. Developed a market test to determine pricing elasticity of various product offerings and collaborated with large cross-functional team to roll-out price changes

Developed Statistical Techniques like Factor, Cluster, Regression analysis and come up with insights

Interpersonal Expertise :

Ability to work with highly sensitive and confidential information

Ability to be flexible with scope of work

Ability to work independently