Deepesh Singh

Experience

• 

  State Bank of India

  May 2013 - Aug 2013

  Intern

  - Worked under General Manager of Central India Zone- Did research on Not Profitable Accounts for SBI- Loss and Risk analysis- Did field survey and submitted report to guide- Hands on with various analytical tools and technique- Developed a model to track defaulters- Provided suggestions on the basis of research to minimize the loss

• 

  Government of India

  Jun 2013 - Jun 2013

  Research Analyst

  - Analyzing the factors effecting voters turn out- Reason for low voting - fear, uninteresting, social pressure, distance etc- Security and safety at voting places- Factors playing crucial role in choosing candidate- How to make election process more effective

• 

  Perennial System

  Jun 2014 - Oct 2014

  Business Analyst cum Development Executive

  - Worked with overseas clients and projects- Handled one of the largest projects of the company- Business analysis, project optimization and resource allocation- Account management and client engagement- Designing marketing campaign for company's portfolio

• 

  Mu Sigma Inc.

  Nov 2014 - Oct 2016

  - Hands-on experience with different analytical tools and languages - R,SAS, Python, Excel, VBA, Tableau- Marketing mix modeling to target the physician effectively- ARIMA modeling for consumer care products sales forecasting across different countries- Solving different pharma industry problems related to SP, Patient adherence and insurance companies- Patient profiling for FDA report to launch a new drug in US market- Performance of different multiple sclerosis centers and physician using location grouping methodology Show less

  • Decision Scientist

    May 2016 - Oct 2016

  • Trainee Decision Scientist

    Nov 2014 - May 2016
• 

  AB InBev

  Oct 2016 - now

  • Currently working on building Assortment solution for one of biggest retailers in Canada for alcoholic beverage products• Using K-means clustering, MNL for demand estimation, Genetic Algorithm for optimization• Built capability for Korea sales team to predict POC churn using Logistics Regression and implemented the same on Azure ML Studio and developed Excel-based API • Leveraged ML techniques like Random Forest and XGBoost to understand POCs’ behaviors where our key brands doing good and where not so good; helped the business to realize $X million• Leveraging the in-house talent to migrate the Korea Sales DB to our local environment using Azure blob, Pentaho ETL and Azure SQL DB• Was part of 2 members delegation to Tel-Aviv to propose our analytical solutions for key business problems• Led 10+ members team to deliver critical Industry Forecasting for 20 markets globally, emphasized the idea of market research, introduced DevOps + wiki and successfully implemented them• Was part of a small highly profiled team to support the research, modeling and strategic decisions made by CXOs during Covid-19 pandemic using SIR and various forecasting models Show less • Worked under Global VP Analytics to build short- and long-term strategies for Global Analytics Center• Conceptualised and curated world-class 'Analytics Academy' which got rolled out to global and around 2K employee registered• Helped ManCom to establish and coordinate governance to ensure global process and guidelines are implemented and followed• Collaborated with Zone Analytics Directors on a weekly basis to bring better synergy and collaboration using HUB & Spoke model amongst the teams situated in 15 different countries• Built PowerApps mobile app to streamline 200+ projects which made greater accessibility, transparency, accountability, and visibility to all stakeholders• Trained self and developed a Looker dashboard in just 10 days for “Champion Global Summit - NY” which was well received Show less • Being the first member of forecasting team, I played a pivotal role to Conceptualize, design and implement our in-house forecasting capability which is leveraged now to deliver 30+ countries and made an impact $XX M• Methodologies used: Time series, ARIMA, Holt-winters, ETS, Linear Regression, Ridge and LASSO, XGBoost, UCM• Built a prototype of Global Forecasting Framework (GFF) using RShiny which is scaled to a full fledge product now• Providing the most granular analysis which helps clients to understand the behavior of industry, market, regions and different brands Show less

  • Principal Product Manager

    Mar 2023 - now

  • Senior Manager Analytics and Product Development

    Sept 2022 - Mar 2023

  • Analytics Manager

    Sept 2020 - Sept 2022

  • Senior Data Scientist

    May 2019 - Sept 2020

  • Global Analytics PPM

    Jun 2018 - May 2019

  • Data scientist, Forecasting

    Oct 2016 - Jun 2018