Senior Data Scientist - Personalization and Recommendation Systems
About The Position
As a Data Scientist in our core AI hub, you will be the core algorithmic engine driving our global personalization strategy. You will deliver advanced recommendation and pricing algorithms designed to increase product adoption and revenue at an exponential scale. To drive success in this role, you must have deep experience ideating, building, and deploying ML systems. As a core Data Scientist, you should be comfortable working with the intricate mathematical details of Contextual Bandits, continuous learning loops, and ML systems architecture. Regular collaboration with our internal Domain Data Scientists and Data Engineers will be key to ensuring your algorithms are adopted globally across our product suite.
Requirements
- Master's or PhD in Physics, Statistics, Mathematics, Computer Science, or other Quantitative fields.
- 5+ years practical, hands-on experience with Machine Learning and statistical testing techniques.
- Deep expertise and hands-on experience building and deploying Contextual Bandits and Reinforcement Learning algorithms in production environments.
- Extensive experience with real-time product recommendation engines, yield optimization, and dynamic pricing models.
- Advanced proficiency in SQL for complex data extraction and Python for modeling and automation
- Exceptional communication skills with the ability to explain complex statistical and algorithmic concepts to internal product and engineering teams.
- Comfortable working in a DevOps environment with a basic understanding of the principles (such as dbt)
Nice To Haves
- Strong problem-solving skills with a focus on building highly scalable software and ML products.
- A systems-thinking mindset. You prefer building a machine that solves a problem 1,000 times over solving the problem manually once.
- A quick learner who embraces new challenges and is not hesitant to push boundaries.
Responsibilities
- Design, implement, and deploy state-of-the-art algorithms for automated yield optimization, with a primary focus on Contextual Bandits, Reinforcement Learning, and Recommender Systems.
- Shape the personalization methodology toward continuous learning systems that dynamically optimize offerings at the user level.
- Build the Personalization Core Frameworks that Domain Data Scientists (in Travel, Digital Commerce, etc.) can easily plug into for their specific partners, eliminating duplicated scientific effort.
- Partner tightly with the data engineering team to ensure models are robustly deployed, performant in real-time latency conditions, and properly monitored.
- Research and closely follow emerging trends in applied ML (specifically in RL and automated yield management) to maintain our competitive edge, acting as the internal subject matter expert for advanced modeling.
Benefits
- Flexible PTO. Taking time out is important for our teams to enjoy life and stay fresh.
- Employee Stock Options - we want our people to share in our success, we reward them with ownership for their contribution in creating a world-class company.
- Work with like-minded people who are passionate about both the work we're doing and giving back. Our CG Gives programs enables us to all become philanthropists through our peer recognition and rewards system.
- Social Initiatives - pictures [https://www.instagram.com/p/B9qnOuUpDVx/] speak a thousand words!
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
