Way of working: The employee needs to come to Bangalore office once a quarter for a week.

Data Science at Swiggy

Data Science and applied ML is ingrained deeply in decision making and product development at Swiggy. Our data scientists work closely with cross-functional teams to ship end-to-end data products, from formulating the business problem in mathematical/ML terms to iterating on ML/DL methods to taking them to production. We own or co-own several initiatives with a direct line of sight to impact on customer experience as well as business metrics. We also encourage open sharing of ideas and publishing in internal and external avenues.

About the Ads Monetization Team

This team is responsible for building and optimizing ML solutions for the full lifecycle of ads across both Food and Instamart Business lines, everything from sourcing the right set of ads to pricing them to targeting them via personalized and multi-objective-optimized user-response models. Ads being one of the highest throughput and lowest latency systems at Swiggy, we are also maniacally focused about delivering pragmatic and scalable solutions.

What you will do

• You will leverage your strong ML/DL/Statistics background to build new and next generation of ML based solutions to improve the quality of ads recommendation and leverage various optimization techniques to improve the campaign performance.
• You will mine and extract relevant information from Swiggy's massive historical data to help ideate and identify solutions to business and CX problems.
• You will work closely with engineers/PMs/analysts on detailed requirements, technical designs, and implementation of end-to-end inference solutions at Swiggy scale.
• You will stay abreast with the latest in ML research for Ads Bidding algorithms, Recommendation Systems related areas and help adapt it to Swiggy's problem statements.
• You will publish and talk about your work in internal and external forums to both technical and layman audiences.

Qualifications

• Bachelors or Masters degree in a quantitative field with 0-2 years of industry/research lab experience
• Required: Excellent problem solving skills, ability to deconstruct and formulate solutions from first-principles
• Required: Depth and hands-on experience in applying ML/DL, statistical techniques to business problems
• Preferred: Experience working with ‘big data’ and shipping ML/DL models to production
• Required: Strong proficiency in Python, SQL, Spark, Tensorflow
• Required: Strong spoken and written communication skills
• Big plus: Experience in the space of ecommerce and logistics