Data Scientist II- Merchandise & Discovery

Key Skills

Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job Description

The Merchandise & Discovery DS team drives personalized ranking of restaurants on the Swiggy Homepage, dish recommendations on restaurant menus, and similar high-impact problems. The team leverages billions of data points to infer the most relevant recommendations for our customers using a mix of traditional ML, deep learning techniques. We are consistently improving our recommendation system by conducting robust offline and online experiments to enable the best ordering experience for our customers. Every single deployment has a positive impact on millions of our customers with extremely high visibility. We encourage high-quality publications/blogs as an outcome of our work and are in a constant mode of learning.

Our team consists of leaders and data scientists who have honed their craft in building recommendation systems at other startups and established companies as well as published their work in top conferences.

What you will do

• You will leverage your strong ML/DL/Statistics background to build new and next generation of ML methods
• You will mine and extract relevant information from Swiggy's massive historical data to help ideate and identify solutions to business and customer experience 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 Information Retrieval, NLP, and 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 audience

Qualifications

• Bachelors or Masters degree in a quantitative field with 2 to 4 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
• Preferred: Experience working with software engineers and familiarity with SDLC
• Big plus: Experience in the space of ecommerce and logistics