Pretty much doing the same work as prior, with the ability to put a little more food on the table now

Lead data scientist for analytics projects undertaken globally within the brewing quality supply space. Roles I play involve strategy, solution architecting and project managementA day here is mostly interacting with teams in each zone working on the projects I own, conversations with senior leaders on strategy and architecture, finding time in between to code on whichever projects that require help, teaching and mentoring on ML and WebDev

Single-handedly designed and implemented an in-house product for test-control experimentation and review. Built with a lot of python (dash) and love. Over a year in development and improving yet everyday. Highlight of my career and the thing that kept me fairly sane across the entire year spent in lockdown

A varied experience working across business problems in the strategy consulting side, to creating products as part of the internal IP development Bain provided a generous platform that enabled me to find my strengths and interests, and the stint, albeit short, added significant maturity and understanding of fundamental problem solvingGained much needed knowledge in the retail space majorly, while also providing opportunities for accruing experience in data engineering and python based web development

Worked as an onsite consultant at one of the largest beverage companies in the world.The major problems i got to work on at the client side were:- developed a global framework to identify and retain employees with risk of attrition- developed and deployed a solution for quantifying the yearly performance of an employee at a global scale (close to 6k employees)As part of MathCo, also managed to accrue experience in Campus hiring and mentoring/training people in the data science spaceDeployed all solutions packaged and scheduled with mostly Python frameworks and in the Azure ecosystem using databricks, datalakes and mssql services

Forecasting project for a food services company to improve logistics efforts with more accurate sales predictionsKey notes:1. Batch forecasting automated to refresh on performance reduction2. Live-fed tableau dashboards for consumption3. Coded in R (arimax), deployed on AWS with a Snowflake databaseRetail project doing batch forecasting of new products and their cannibalization of existing products. Part of the process involved in deploying them into the digital platform backend- NPD forecasting of 1000's of SKUs across ~41 product categories- Employed several feature engineering, selection and modelling in the pipeline (xgboost, random forest, arima)- Process devoloped in R, and later translated to Python for deployment- Seperate processes created for Similar product clustering and cannibalization for NPDsPrimary contributor in a novel project for a huge Swiss bank, involving generating synthetic test data for offshore app-development, with minimal touchpoints with production- PL/SQL codes and XML logs of the scheduler were parsed and translated to usable information in R- 14 primary tables generated with random test data in the end that gave a coverage of ~95% code coverage and 75/120 business rules coverage- Process was made as dynamic and scalable as possible as to be leveraged across other applications/regionsConsolidation project for a major footwear company to integrate their manufacturing supply/demand dashboards/workflows- Involved Teradata, Tableau, R and Alteryx primarily- Validation/QC modules created in R connected to Teradata- Created migration tools to do batch migration of tables from Teradata to Snowflake using R and Alteryx, using AWS-s3 for staging

Part of a customer churn/retention problem, creating a prediction model for a major insurance client to help make low level decisions easier, and scaled for their entire Asia - Pacific region- Created the foundation for enabling machine learning based decision making for their global analytics department (platform - R)- 4 monthsCreated Excel VBA automation tools, Qlikview decision boards for one of the biggest life insurance companies as part of a process of optimizing their business. Prototype towards creating value for their Russian entity- A simple automation project that brought down a 4 hour a day manpower usage to a minute (VBA tool)- A Qlikview decision board to manage doctors within their health case management system (complete doctor management system)- Handled the discovery phase towards identifying viable opportunities for their Russian business with extensive collaboration with the Russian stakeholders- 10 monthsPresales experience in both pitching and handling discovery phase of projects across insurance, retail and government transportation domains. One specific one being for a US state department of transportation, in partnership with a leading design consultancy firm- Did a prototype for a US state department of transportation to create a strategic/heuristic based model towards efficient selection and prioritization of transportation projects- 3 months