About the Team:

Data Science @ Cars Commerce is a group of collaborative and humble individuals from diverse backgrounds. We are actively involved in the open source community and regularly participate in Data Science events. We learn from each other through regular algorithmic/code review sessions and stay connected through coffee chats in this remote world.

About the Projects:

We deliver scalable ML products that are served to millions of users through our website and mobile app. Search, Recommendation Systems, Pricing and Churn are some of the example projects that we actively work on. Right from the start, each team member will own a product(s) and as the time progresses, you will gain exposure to working on diverse areas of ML. The team maintains a healthy balance between research projects and immediate deliverables.

On a typical week you will:

• Collaborate with product and engineering teams to define, design, build and deploy machine learning models and frame AB tests 
• Understand business impact of models and monitor model performances to make sure model outputs are of good quality at all times 
• Apply robust and maintainable coding practices to ensure model outputs are provided reliably and efficiently at all times
• Work with business partners to identify business opportunities and trends
• Communicate modeling methodologies and analytical findings to business stakeholders 
• Stay up-to-date with latest technology trends and publish research articles on science and innovations

Requirements:

• 2+ years professional experience in developing machine learning models with a MS in machine-learning, applied mathematics or related quantitative fields
• Understanding of supervised, unsupervised machine learning and deep learning concepts
• Exposure to and understanding of GenAI concepts, models and tooling preferred
• Experience with entire pipeline of deploying machine learning algorithms including development, validation, implementation and production launch
• Strong coding skills in Python/PySpark and good at writing SQL queries
• Understanding of AWS ecosystem
• Be flexible in working on diverse problems instead of focusing on a particular ML area like Image Recognition, Natural Language Processing etc.
• Understanding of coding best practices and familiar with version control tools 

Preferred:

• PhD/Masters in statistics, econometrics, machine-learning, applied mathematics or related quantitative field
• Experience in building end to end Machine Learning systems

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