Senior ML Scientist

**Data Science @Dream Sports:**Data Science at Dream Sports comprises seasoned data scientists thriving to drive value with data across all our initiatives. The team has developed state-of-the-art solutions for forecasting and optimization, data-driven risk prevention systems, Causal Inference and Recommender Systems to enhance product and user experience.
We are a team of Machine Learning Scientists and Research Scientists with a portfolio of projects ranges from production ML systems that we conceptualize, build, support and innovate upon, to longer term research projects with potential game-changing impact for Dream Sports.
This is a unique opportunity for highly motivated candidates to work on real-world applications of machine learning in the sports industry, with access to state-of-the-art resources, infrastructure, and data from multiple sources streaming from 250 million users and contributing to our collaboration with Columbia Dream Sports AI Innovation Center. Your Role:

• Executing clean experiments rigorously against pertinent performance guardrails and analysing performance metrics to infer actionable findings
• Developing and maintaining services with proactive monitoring and can incorporate best industry practices for optimal service quality and risk mitigation
• Breaking down complex projects into actionable tasks that adhere to set management practices and ensure stakeholder visibility
• Managing end-to-end lifecycle of large scale ML projects from data preparation, model training, deployment, monitoring, and upgradation of experiments
• Leveraging a strong foundation in ML, statistics, and deep learning to adeptly implement research-backed techniques for model development
• Staying abreast of the best ML practices and developments of the industry to mentor and guide team members

Qualifiers:

• 3-5 years of experience in building, deploying and maintaining ML solutions
• Extensive experience with Python, Sql, Tensorflow/Pytorch and atleast one distributed data framework (Spark/Ray/Dask )
• Working knowledge of Machine Learning, probability & statistics and Deep Learning Fundamentals
• Experience in designing end to end machine learning systems that work at scale