Rohit Rajkumar Dhonukshe
Data Scientist | Python, R, SQL | Machine Learning | Deep Learning | Statistics & Econometrics | Data Analytics | E-commerce | Sponsored Ads | Marketing Science | MS in Data Science
- Role
- Data Science Consultant at eBay
- Location
- New York, NY, US
- LinkedIn followers
- 500 followers
About Rohit Rajkumar Dhonukshe
I’m a Data Science professional with expertise in machine learning, econometrics, and…
Experience
Data Science Consultant
Aug 2023 — Present · US
Designed and executed a control experiment comparing AI-recommended vs. manually created Ad campaigns. Applied Fixed-effect Regression, Marketing Mix Modelling to analyze performance data, revealing superior results from manual campaigns, demonstrating the value of sellers’ private information in campaign optimization.• Spearheaded the Quantitative analysis on the impact of the Promoted (Sponsored Search) Ads channel on seller performance using R, utilizing Causal Inference technique - Propensity Score Matching to identify adopter, non-adopter seller pairs of the new Ads channel.• Conducted hypothesis, A/B testing, Average Treatment Effect on diverse seller data (performance history, product portfolio), uncovering statistically significant improvements in net sales, clicks for channel adopting sellers in 2023.• Implemented Staggered Difference-in-Difference model to predict Sales Uplift of Ads channel adoption, by determining Conditional Average Treatment Effects of Sponsored Search on seller performance, enabling targeted recommendations for high-potential sellers.• Conducted PCA on items’ leaf category features to derive principal components, enabling more granular control in the comparison of AI-recommended and manually created ad campaigns, further validating the superior performance of manual campaigns.• Developed Causal Trees, Causal Forest (Generalized Random Forest) model to determine the effect of match types (exact, phrase, broad) on clicks, revenue, identifying seller segments, item categories, keyword groups where specific match types drive optimal performance.• Developed a specialized Data Mart within Hadoop ecosystem (HDFS) using SQL, Spark, ETL processes, significantly accelerating analytical research by providing streamlined access to relevant datasets.• Investigated seller dynamics of the advertising channel by visualising trends with Python, Matplotlib, identifying a 12% average monthly churn rate and 17% new seller adoption rate.
Education
Indiana University Bloomington
Master of Science - MS, Data Science
Motilal Nehru National Institute Of Technology
Bachelor of Technology - BTech, Electrical and Electronics Engineering
2018 — 2022
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