Svp - Data Science Job in Dream11

Technology @ Dream11Our tech team is the core of Dream11s mobile-first cross-platform (desktop + mobile PWA, android & iOS) product serving more than 8 Crore users with over 50 million rpm (requests per minute) at peak concurrency.Our tech stack is hosted on AWS and is built on Cloudfront / AWS API Gateway, NGINX, Node.js / Java, Redis / ElastiCache and MySQL / Cassandra as our end to end stack. Besides these, we heavily use MongoDB, Kinesis, Kafka, RabbitMQ, Spark, Redshift and other cutting edge tech to keep improving Dream11's performance. As a data-driven team, we also use R, Python and other big data technologies for Machine Learning and Predictive Analytics.

Your Role:

• Leverage your ML industry expertise to introduce new technologies and processes, and drive innovation within Dream Sports' product offerings
• Provide direction for building ML driven systems across different product categories
• Shape, grow and lead the team that delivers novel, strategic ML solutions
• Lead ML research and development of tooling in statistical modelling, recommendation systems, deep learning, computer vision, natural language processing, and data engineering, using state-of-the-art approaches
• An eye for product and relentlessly putting the customer at the heart of your strategic decisions

Must Have:

• Education in Machine Learning or Numerical Computation/High performance computing related fields
• Overall experience of around 10-15 years and ~5-7 years of experience in the Industry in providing Machine Learning Solutions
• Experience in a product set up & passionate about driving results via experimentation backed data initiatives
• Deep technical background in applied machine learning, including recommendations systems, deep learning, computer vision, and natural language processing

Good to Have:

• Distributed Machine Learning Experience
• Have spent some years working as a Software Engineer and Data Engineer
• Previous experience in building end-to-end machine learning pipelines, including algorithms and tooling
• Published researcher with a strong track record of academic experience in ML and AI
• Active Open Source Contributions into Machine Learning or Numerical Computation libraries
• Experience with building Machine Learning / Experimentation based systems
• Sports Fan