Headline

Data Scientist | Master’s in Statistics

About

Data Scientist at Accenture strategy and consulting

Location

Mumbai

AI stack

aistudio

hugging face

notion

openai

Work experience

Data Science Analyst at Accenture Strategy & Consulting, Aug 2024 - Present · 2 yrs 1 mo, Mumbai, Maharashtra, India, I work as a Data Science Analyst at Accenture where I mainly work on marketing analytics and Market Mix Modeling projects. My role involves analyzing marketing performance across different channels like TV, digital, and other media to understand how each channel contributes to business outcomes such as sales or revenue. In these projects, I work with large marketing datasets and help build models that estimate the impact of different marketing channels. This includes applying transformations like adstock and saturation to capture how advertising effects decay over time and how channels reach diminishing returns. I also spend a significant amount of time validating the data and model assumptions. For example, checking for multicollinearity between channels, ensuring the model residuals behave correctly, and making sure the results make business sense. Once the model results are ready, I help translate the technical findings into actionable recommendations for the business. This usually involves identifying which channels are saturated, which ones have higher marginal returns, and how the marketing budget can be reallocated to improve overall efficiency. The goal of the work is to help clients make more data-driven decisions about where to invest their marketing budget to maximize revenue impact

Data Science Intern at Accenture, May 2023 - Jul 2023 · 3 mos, Mumbai, Maharashtra, India, I recently completed a 2-month internship at Accenture AI, where I worked in the Marketing Team. During my internship, I focused on providing solutions for various ID Resolution scenarios. I created graphs using Neo4j and Databricks to address both deterministic and probabilistic ID Resolution problems. One of the key projects I worked on involved Customer Data Architecture (CDA), which combines multiple customer data sources into a single, cohesive view of the customer. In this process, we collected various customer identifiers and assigned them to a universal ID. We utilized graph databases, the industry standard, to implement and manage this identity resolution

Education

Master's degree, Statistics, INDIAN INSTITUTE OF TECHNOLOGY KANPUR

Bachelor's degree, Statistics, Delhi University