I am a Data Science Consultant with 4.5+ years of experience in delivering data-driven solutions across CPG and Retail
domains. Skilled in Python, PySpark, SQL, and Azure for building scalable machine learning models, automating big
data pipelines, and deriving insights from complex datasets. Proven expertise in pricing promotion analytics, MMM,
and stakeholder engagement.
This RGM Project required us to provide end to end value insights and support to client regarding Pricing,
Promotion, Distribution and overall how they affect the revenue. We developed and maintained over 60
Reports and Simulators on Power-BI, Excel and React to be utilized everyday by client. We used Nielsen
POS data, Internal financial data and our model outputs for that.
We had a robust Pricing and Promotion Bayesian Regression model for predictive analytics. Ranging over
2.5 years with this client, Feature engineered various modelling variables like Media Variables and Panel
data(House hold penetration) into the model and was responsible for Model Validation.
Developed logic and Coded several analytics reports including NPOD, Price index Traffic light, Elasticity
tool, waterfall tool, length and frequency , Next best action tool to name a few. Leveraged Pyspark to
handle weekly Big Data of over thousands of SKUs/UPCs and around 250 PPGs.
Created Pipelines and Triggers on Azure DataBricks for regular refreshes to incorporate latest data. Lever-
aged Databricks for version control and data quality control.
Utilised SQL/SSMS to create and manage Relational data for Demand and forecast handling of over 23
retailers incl. Walmart. Collaborated with Full stack developers to implement authentication base React
APIs to real time track actualized demand and new forecast numbers happening periodically.
As a consultant, understood client problem statements and led a team of 3-Data engineers to handle every-
day ad-hoc analytical requirements. Led team of Power Bi Analysts to create Dashboards and Volunteered
to emulate US Power bi Dashboards for Canada market POC which eventually led to Full scale billed project
.Helped client realize value of over 270 Million Dollars over 2023-24.
Client: US-Europe Spices and Condiments Comapany
Service: Marketing Media Modelling(MMM)
Created a full scale MMM Project which focuses exclusively on Media promotions like Facebook/Instagram
ads, Google Search, Newpapers ads, Hoardings etc. Utilized Excel full potential incl. Visual Basics(VBA) to
created Bayesian model over Excel for client understanding.
Feature engineered important media attributes like Video promotion length(5 sec/ 1 min etc), influencer
flag to test their efficacy on a marketing campaign. Utilised statistical tools to curate variables with high
correlation with revenue and bring variance to the equation.
Simulated spends vs ROI for several planned media campaigns. Suggesting ideal budget in accordance with
saturation curve for maximum potential Profit ROI over assigned budget.
Client: Prominent Hygiene and Homes CPG Company for Australian Market
Service: Pricing and Promotion Modelling
Pricing and Promotion models focus on everyday TPR (temporary price reduction), Display, Feature promotions, and ACV distribution run by Manufacturer-Retailer for a product.
Developed ElasticNet regression model (combination of Ridge + Lasso regression) for improved model fit and explainability. Created Due-tos waterfall to explain base sales and Promotion uplifts.
Provided advanced analytics like price change suggestions with respect to product elasticity, self-competition product cannibalization, and price ladder-price gap to reduce it.
Created dashboards for price tracking, opportunity identification, promotional ROIs, retailer margins, and manufacturer margins.
SpeedLabs Indore, MP, India (Machine Learning Intern)
May 2019 – June 2019
SpeedLabs is an AI-based online lecture and practice platform focusing on Competitive exams like engineering and medical entrances like IIT JEE and NEET etc.
Helped curate new tools for the platform. Reviewed and corrected errors on the platform’s content.
Developed content targeted to JEE exam. Proposed feedback regarding the platform structure, user interface, user experience.
Visited Schools, Pitching them about what AI-tool has to offer, and how it can help students to crack their dream colleges.
Ultratech Cements Tadipatri, AP, India (Research Intern)
May 2018 – June 2018
Conducted experimental testing to analyze cement strength and consistency.
Effect on strength, durability, and consistency of cement examined vs varied particle sizes/Blaine number.
Performed Autoclave test, Le-Chatelier test, strength test, and Blaine number analysis to determine particular Blaine performance.
Results were tabulated and examined on an Excel database, with various analytical charts to explain the output.
Results showed 300m²/kg and 350m²/kg Blaine number respectively for OPC and PPC as a higher end for hardness with optimal costing.
Skills and Certifications
Programming
Python, PySpark, SQL, Visual Basic (VBA)
Data Science & Analytics
Machine Learning, Predictive Modeling, Deep Learning, NLP, Statistical Modeling
Feature Engineering, Data Cleaning, Data Storytelling, Simulation Modeling, Automation
Tools & Platforms
Excel, Power BI, Azure Data Factory, Databricks, Azure DevOps, Git, SSMS, Figma
Certifications
PG-Diploma in Data Science – IIIT-Bangalore
Microsoft Certified: PL-300 Data Analyst Associate
Microsoft Certified: DP-900 Azure Data Fundamentals
Automated Mediator Power Socket, MARS, IIT Roorkee
Created a portable home automation device that plugs between a power socket and cord, enabling control via
a smartphone app. The product, built using Node-MCU and a relay module, offers a cost-effective and portable
alternative for turning devices on/off and setting timers. Presented at SHRISHTI’18, IIT Roorkee
Youtube Parser Scraper
Developed a Python-based scraper using Selenium and BeautifulSoup to extract video metadata, including titles, descriptions, and tags. Incorporated Natural Language Processing (NLP) techniques to analyze and summarize video descriptions for better insights.
Resume
LinkedIn
GitHub
