Candidate's About
I am an Analytics & Research Professional with 7+ years of experience in executing data-driven solutions that help businesses increase the efficiency and utility of internal data processing. I have created data regression models, used predictive data modeling, and analyzed data mining algorithms to deliver insights and implement action-oriented solutions to business problems.
Work & Experience
SStaff Engineer (Data Science Engineer)
Sep 21 - PRESENT
- Developed a sophisticated Market Mix Model for a leading automotive company, leveraging machine learning techniques to evaluate marketing strategies impact on car sales.
- This project involved creating a multiplicative regression model to accurately forecast sales based on a mix of media investments and macroeconomic indicators, optimizing for maximum ROI.
- Effectively utiliz...
Read More SStaff Engineer Data Science Engineer
Sep 21 - PRESENT
- Build multiple Dashboards on Power BI to analyze engine performance of cars
- Provide ongoing analytical support using data management and technology to address client issues regarding data integrity
- Collaborate with Data Engineer to build end-to-end CI/CD pipelines using Redshift for ML models
- Build classification models using machine learning techniques (random fore...
Read More SSenior Analytics Engineer
May 19 - Sep 21
- Provide measurement, reporting, and analytics for digital media, website, CMR, and offline activities
- Monitor key trends and metrics to identify areas for operational and marketing improvement
- Develop and apply advanced analytics to areas such as marketing testing, yield optimization, marketing mix modeling, and attribution
- Develop and maintain analytical tools (R a...
Read More SSenior Data Analyst
Sep 18 - Jan 19
- Understood and articulated business problems into technical solutions, providing the required output
- Provided Machine Learning solutions to stakeholders using R and Power BI
- Utilized text mining skills on social media data, including NLP, topic modeling (using LDA), and sentiment analysis
SSenior Research Analyst
Apr 16 - Aug 17
- Conducted primary and secondary research and generated and qualified market analytics/research
- Profiled accounts by finding facts such as which hardware and software applications each prospective company had installed
- Monitored and updated information related to leads, contacts, accounts, and account hierarchies in CRM to maintain a clean and structured database
RResearch Analyst
May 15 - Jan 16
- Collected data on consumers, competitors, and the marketplace and consolidated information into actionable items, reports, and presentations
- Sourced relevant and accurate information through secondary (including databases) and primary research
DData Analyst
Jan 14 - May 15
- Created reports that provided information on business activity
- Reports may have been daily, weekly, or monthly and may have included data, graphics, charts, pivot tables, etc. using Excel.
Education
MBachelor of Commerce
Manav Bharti University2011 - 2013
MPost Graduate Diploma in Data Science
Maharishi University of Information Technology2017 - 2018
Certificates
DData Manipulation in R
DataCamp DDigital Marketing (Google Certified)
DSIM Delhi Achievements
- Conducted research using focus groups on 3 different products and increased sales by 11% due to the findings.
- Built a model that determines the polarity of tweets (using Paytm's Twitter handle and creating a Twitter API) by using text mining, web scraping, and sentiment analysis to classify words as negative or positive.
- Developed key performance Indicators to monitor sales and decreased costs by 17% for a renowned Automotive premium segment giant.
- Predicted the Percentage of loan approval by a bank on Analytics Vidhya (Score- 0.7847)
- Built an algorithm to keep the users engaged on the platform by their authors so that they can solve the problem (which were developed by authors) on Analytics Vidhya (Score-0.010439).
- Predicted the Sale Price for each house on Kaggle (RMSE = 0.17608).
- Forecasted future sales of an automobile company for the next 36 months using ARIMA.
- Analyzed various data sets such as e-Commerce, Retail, Web Server, and Game Portals.
- Completed market analysis for one of the US-based retail giants, resulting in a 21% increase in sales.
- Predicted survival on the Titanic from Kaggle dataset with a GINI coefficient of 0.18.