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.
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