I am a Data Science & Engg. Manager at Dish,
the world's largest satellite television provider.
Previously, I worked at Evalueserve and Mu
Sigma as a lead data scientist across industries like CPG, retail, manufacturing, airlines and
fintech.
I maintain a list of the stuff I enjoy reading, watching, or learning from called The Knowledge Bank and occasionally blog here.
I am an AI/ML leader at DISH India, leading a team of 14 people across science, engineering and analytics. My team works in the technology, marketing, sales and operations verticals. I am currently hiring - so if you are a good fit, shoot your resume here.
I lead a team of 22 data scientists for multiple engagements across retail, food and beverage and energy sectors. Currently, I'm built a voice agent for a fast-food giant using advanced neural networks and NLP - parallelly working as the head of a AI CoE which executes pilot engagements for new clients.
• Developed & deployed a MMX solution which manages $230M/yr. across 17 channels
• Uses a combination of ridge regression-based attribution model and non-linear optimization
• 2.4% lift in activations compared to BAU allocation–reduced SAC by 4.8%
.
• Built the DCO solution for serving dynamic creatives to prospects, optimizing elements in realtime
• Developed the ML web service using AWS Lambda, DynamoDB, API Gateway & CloudFront – which
stitches and delivers creatives (HTML/JS Zip bundle) to ad serving platform
• Implemented Bayesian Bandits for continuous optimization of elements towards higher CTR
• ~39% CTR uplift, 0.9% acquisition uplift, and savings of 290 hrs./qtr. Effort
• Developed a chatbot using RAG and LangChain for querying Confluence documentation of tech
teams; uses LLama2 7B as the base model, ChromaDB vector store and FAISS for similarity search
• Experimented with PEFT (LoRA/QLoRA) based fine-tuning - but no significant improvement over RAG
• Currently finetuning on Mixtral MoE 8x7B Model using Direct Preference Optimization (DPO).
• Developed the Smart Bidding Algorithm which optimizes for spend on high ROAS patterns (‐17%SAC)
• Led MTA (Multi Touch Attribution) initiative to enable holistic view of channel ROAS
• Built subscription & viewership forecasting model > led to +0.12 AUC for downstream churn models
Lead a team of 6 analysts in a $1.3MM engagement to build a sales force planning and optimization tool to maximize sales uplift or ROI and reduce expenditure. We have clustered outlets, measured impact of visits using a regression model and designed a Mixed Integer programming (MIP) based optimizer to generate visit plans. We have also designed a planning & reporting tool using PowerApps to design plans and report results. Potential impact of ~3% incremental sales uplift(+$6.2MM) and sales force expenditure reduced by 24%($0.5MM) – and savings of 960 hours/quarter effort.
Working for a leading CPG manufacturer, we created a sales driver model for attribution of sales volume to key imperatives using ElasticNet regression. We developed a Trade Promotion Optimization (TPO) framework which enabled the Account teams to design optimized promo plans leading to reduction of ~2100 hrs. of manual effort/quarter. The framework is powered by a linear optimizer on the sales driver model & builds a 52-week calendar detailing optimal price points, ideal promotion weeks, and optimal execution distribution points
Developed a Competitor Clash Forecasting framework to help account managers design promotions in accordance with forecasted competitor prices. The framework uses ARIMAX models to forecast the prices of competitor products and uses these prices to predict manufacturer and category sales through a regression-based sales attribution model. Captured a 30% reduction in negotiation time and sales uplift of 2%($3.6MM) across four retailers in six months
Implemented CNN based YOLO object detection algorithm for a video occasion detection tool – to detect the class and number of objects present in a scene with a mAP of 51.5%. Additionally, we also had to design a XGBoost model to classify a scene into consumption, transaction or celebration based on the class and number of objects detected by YOLO. This was an industry-first dataset for Consumer Behavior Data and acquired by a Global Beverage Giant for ~$5MM
Designed a Neo4j graph database based digital fingerprinting model which identifies unique users across anonymous devices leveraging behavioral relationships. The ideas was to classify new anonymous user IDs into either a current user or "new-to-platform" users. We reduced advertising expenses by $0.8MM/month by reducing number of targeted users
Building rich 3D maps of environments is an important task for mobile robotics. In this project a quadcopter and a Kinect™ camera are used to perform Simultaneous Localization and Mapping. Rich 3D maps are built using RGB-D to generate dense models of indoor environments. The detailed project report can be found here. A presentation is also available for a more gentle introduction.
Wrote a GUI, an orbit analysis tool, and did some code factoring on a simulation for a nanosatellite that will actually launch into space in a few years.
I've been fortunate to have been in involved with Prof S. N Omkar in Robotics and Machine Learning, and am currently in the process of getting a research paper published.
I am a volunteer at ALIG, a national level NGO which is working on social entrepreneurship, education and health in India's hinterlands.
I organized a pre-placement workshop for my juniors. This workshop had sessions ranging from profile building, resume writing to mock interviews. It was a big success and the team involved got a lot of praise for it.
I am a regular editor on Wikipedia, going by my pseudonym Oakshade. I have already edited around 15,000 articles and am currently ranked 4,996 on Wikipedia Editor List.
I have raced professionally on the Kari Motor Speedway & in go-kart championships. I've also authored a small handbook on track racing, which can be downloaded here. My love for four-wheeled action is infinite, and my weapon of choice is my beast.
My Myers-Briggs Type Indicator(MBTI) is ESTJ [Extroverted Sensing Thinking Judging]. The favorite people I supposedly share my personality type with are Henry Ford, Hillary Clinton and Michelle Obama. You too should take the test here.
I enjoy blogging and reading about tech. I'm compiling a list of my favorite books, videos, articles and news sources on the internet in a list called The Knowledge Bank. Reddit has become one of my most integral source of news.
I am a flight simulation enthusiast and currently serve as a First Officer in Virtual Air India. I usually fly the Boeing 777 on long haul routes. I have recently started flying short hauls in the Boeing 737 as well.
I love playing Counter Strike Source and go by the name Hitman. I am currently ranked 761 out of 176063 players in CSS World servers. Maximum kills recorded were 407, in an all-nighter match like this one.