Dec 2022 – Jun 2024 · 1 yr 6 mos · Bengaluru, Karnataka, India · Hybrid

• Worked with projects involving Demand Forecasting, Inventory Optimisation, Assortment Planning and Store Normalization.
• Spearheaded research in areas of Time Series Clustering and Forecasting.
• Worked on a Demand Prediction application to predict the market demand of a new style/product before it hits the shelves to power New Product Introduction (NPI) planning.
• Worked on automating workflows for dashboard generation and styling using python.
• Working on software system design and implementation of trend analytics engine.
• Awarded "Superstar of the Month" x2 for commendable ownership and performance, awarded Value Champion award for upholding and showcasing company values.

Jun 2022 – Dec 2022 · 6 mos · Hyderabad, Telangana, India

• Led analytics for the Driver Experience team for India & South Asia.
• Executed strategies for rewarding good payment behaviour by use of predictive modelling leading to cut down on nationwide losses, reduction in driver churn and increase in retention rates by ~10%.
• Orchestrated flows and handled 50+ mission critical script automations (crossing 1.5lac monthly runs) concerning near real-time driver payments and actioning.
• Optimized driver payment experience by developing processes to improve payment recon times by ~30% and boost collection rates by ~5%.

Jan 2022 – Jun 2022 · 5 mos

• Worked with the CPG team on development & deployment of production-grade reactive ML web applications using Streamlit / Dash / RShiny frontend & Python models as backend;
• Executed R&D for predictive modelling and designed reusable routines to automate the machine learning workflow within the same, achieved ~20% mean uplifts of performance metrics on status quo techniques.
• Worked on development of an in-house Automated ML platform with use-case specific customizability as a feature, in turn delivering end-to-end predictive and descriptive analytics as a service.
• Worked on a POC project on Clustering of Retail Stores for targeting discounting strategy and recommending stock inventory thereby securing a high-value client for the company.
• Worked on process and memory optimization for Market Mix Modelling, achieved ~40% reduction in mean runtimes.
• Certified as ’Expert’ in Structured ML, PySpark, AzureML and Python by Team SCaLA.

Jul 2021 – Dec 2021 · 5 mos

• Supervised SCaLAthon Awardee - Winner (Hackathon on Supervised ML - Loan Default Prediction to reduce NPAs in banking).
• Time Series SCaLAthon Awardee - Winner (Hackathon on Time Series Analytics - Volume Sales Forecasting)
• Recipient of 'BU SuperHuman - Peer Award' for Q3'21.
• Top 8 in Accendo Hackathon '21 - Presenting ideas for AI in the new normal.
• RAM (Reusable Asset Management) Contributor.

Aug 2020 – Jul 2021 · 11 mos · Bengaluru, Karnataka, India

• Worked with the CIFS/AFP protocols team of Open Enterprise Server (OES) product as part of the File & Networking group [inside Novell].
• Responsible for identification and execution of test plan, strategy and management; estimation & authoring of test requirements and scenarios; designing of requirements traceability matrix; defect reporting & tracking, and follow-ups with dev & business teams.
• Processes & Tools worked on: SLES 12, Linux, JUnit Automation, Python Scripting, Functional Testing, Feature/Component & Regression Testing and other types of testing covered as part of Agile DMLC (Defect Management Life Cycle), Anomaly Detection, Clustering and other unsupervised methods.

Jan 2020 – Feb 2020 · 1 mo · Bengaluru Area, India

• Worked on several WebApp Development projects in SharePoint (2016).
• Built Client Side Object Model (CSOM) web-parts for a subsite tool within the company's intranet site.
• Stack used: dHTML- JavaScript & jQuery+AJAX, and SharePoint Customs List at backend.