Data and Artificial Intelligence leader responsible for delivering data product solutions to the Merch, Digital, Supply Chain, Marketing and Global Insights verticals.Led DS, DE, MLE and SDs to build in-house solutions for business verticals. Sample Data Products include;- Customer Explorer App - A UI/UX application flush with backend access to ML models and 1000+ engineered features to generate an audience to be targeted primarily for FoS marketing campaigns.- Marketing ML Models - Several ML models based on Marketing business requirements that segment Walgreens clientele for Rx/FoS paid and owned media campaigns.- Master Aggregate Data - An Aggregation of business critical base tables leveraged by teams to glean quick insights in decision making, integrate in downstream solutions, dash-boarding, etc.- Credit Card Propensity Model - ML model that targeted customers who were likely to accept and use Walgreens cc, an improvement over the existing QS process.- Retail Working Capital (RWC) - Store inventory optimization ML models that support store product stocking decisions based on market trends, business rules, etc.- Value Platform - Developed ML models that target customers with personalized offers at their most frequent neighborhood store- Micro Space Optimization - ML model developed to optimize revenue vis-a-vis limiting store real estate.- Product Recommendation Engine (PRE) - Developed in-house PRE ML models to replace default models embedded in Adobe Target after A/B testing of champion and challenger models on real time consumer traffic.- SVOC (Single View of Customer) - Several dashboards that provide insights into customer FoS, Rx and Cross shop behavior.- Enhancing Search - Provisioned data to enhance the Algolia engine supporting Walgreens product search.Loss Prevention - POC’d ML models to reduce shrink resulting from employee misconduct.

- Data Quality EngineDesigned the micro service architecture for auditing product/item attribute data to remove erroneous information uploaded by vendors during product onboarding.Led a team of data scientists to develop algorithms to remedy various error types (e.g., incorrect product image, superlative claims, missing supporting documents, etc.) that populate product catalogues because of vendor errors.Worked across teams (data engineers, GCP support group) and the business to ensure micro service SLAs (300k new items/product onboarded per day, system stability) were met. This resulted in the business adopting the tool my team built due to its superior performance in lieu of an existing third-party tool.Led discussions with the business and suggested Data Science solutions to the myriad data quality challenges in the organization.- Omni-channel Text Analytics PlatformLed a team of data scientist to build a dashboard that generates insights from Lowe’s VoC data using NLP techniques.Developed topic modeling, sentiment analysis, entity and intent extraction models to derive customer feedback trends such as customer service (dis)satisfaction rate, Net Promoter Scores (NPS), etc. that offers the business a sense of how well customers are interfacing with Lowe’s business strategy.Product Safety Classification ML models to classify product reviews that discuss injuries or potential injuries due to product usage by customers.- Space OptimizationWorked with a team of data scientists to develop Mixed Integer Programing (MIP) and Genetic Algorithms (GA) to optimize the number of products from similar assortments that can be packed into a given shelf space to optimize sales/revenue.

Exception Based Reporting (Store Simplification)Worked with a team of data scientists to develop algorithms that simplified the core metrics a store manager uses to assess one store performance in comparison to other stores within similar demographic locations.Applied forecasting models to predict store performance based on varying core store operating processes such as leads, credit cards signups, pro, out of stock, attachment rate, LTR scores etc. These models generated score cards for store managers to assist them adjust store operations that will enhance sales/revenue on a weekly basis.

Development of computational fluid dynamic models for fluid flow and heat transfer processesProduce/import CAD geometry into CFD model, clean geometry and generate computational meshWork with CFD software programs including ANSYS Fluent, ANSYS CFX and other related modeling software to model physicochemical processesIdentify major transport mechanisms and develop computational tools from first principles using C/C++, MATLAB and other programming languagesPerform parametric studies to investigate effects of various design and operating parameters

* Research on Computational Fluid Dynamics Modeling of Biomass Gasification in a Fluidized Bed Reactor* Conducted Experiments on Fluidization of Biomass - Sand Mixture to understand the effect of bed hydrodynamics on gasification process* System/Server administrator for the Computational Fluid Dynamics Simulation team at the NSF-CREST Thrust 1 (Gasification Project) Group* Facilitator/Tutor of Biological Engineering Laboratory classes* Coauthored book chapters: "Sustainable Bioenergy Production - Cat/ISBN: K14570/9781466505520"

* Researched on Pretreatment and Fractionation of Biomass for Biological Production of Transportation Fuels and Value Added Chemicals * Graded homework assignments of undergraduate students* Tutored and assisted undergraduate students to better understand course materials* Engaged in assisting undergrads to conduct required laboratory experiments as part of their Chemical Engineering training

* Consulted for small businesses in the design and fabrication of production units* Taught AutoCAD drafting software as a better modeling tool* Prepared reading materials and curriculum for participating students* Conducted end of training exam for participating students* Graded exams and assisted in awarding certificates to participating students