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Associate Data Scientist

No matter where I go next, no organization can surpass the people and culture of my current company. I began my analytics journey here, growing from an analyst to leading a team. I’ve gained experience in the automobile, CPG, and social journalism domains, and accumulated expertise in Python, statistics, SQL, and machine learning. My role has also involved delivering data-driven decisions, modeling, client communication, and project management. Additionally, I’ve learned various tools such as dashboarding, Jira, AWS, Looker, and Snowflake.

Roles and Responsibility

  • Deployed an Assortment Management tool for a CPG client to help Category Strategist in creating priority list for national, channel, and retailer levels using company’s in-house dashboard. The tool is able to improve the efficiency by 70% in creating priority lists, leading to faster decision-making
  • Led the team in System Design, Database Creation, and PEP8 standards implementation for the Assortment Management tool
  • Assisted the team in scaling of the data pipeline in order to accommodate demand transference model for over 200+ combination of categories and retailers
  • Conducted impactful analysis and Deep Dives, delivering solutions through intuitive dashboards for the Platform, Mobile, and Revenue Teams of a social journalism client, resulting in a 16% boost in platform engagement over the next quarter
  • Developed an Automated A/B Testing framework with the Mode dashboard, facilitating the creation and testing of over 5 experiments per sprint. Ensured statistical significance in assessing impact against KPI metrics, encompassing reader metrics, member conversion, and adoption rate
  • Engineered a tailored dashboard integrating all pertinent reader metrics, member conversion, and adoption rate, resulting in an increase in the client’s ability to actively monitor and analyze ongoing changes in live A/B testing experiments
  • Deployed a Price Elasticity model for an Automobile client to help the Brand managers optimize vehicle prices to maximize their share and profit
  • Led Hypothesis testing, coupled with EDA, to validate new features for integration into the Price Optimization model, resulting in a significant 30% increase in the R2 score
  • Spearheaded Knowledge Transfer sessions on Statistics, Python, and SQL for over 300 interns.