Machine Learning Scientist

About the role

WHY DATA SCIENCE AND ANALYTICS

The Data Science & Analytics organization's mission is to increase our speed, frequency, and acumen in making decisions at scale by instilling a data- influenced approach to building products. We cover a wide area of the data spectrum, including analytical data engineering, product analytics, experimentation, causal inference, statistical modeling, and machine learning. Aligned and partnering with product verticals, we use this extensive tool belt to discover new opportunities and unmet use cases, influence and shape the product roadmap and prioritization, build data products, and measure impact on our community of players and developers.

In Data Science & Analytics, you will contribute to horizontal ML systems and infrastructure that enable us to understand the trajectory of users and creators as well as the overall business to inform investment opportunities and accelerate our growth. These systems inform experiment decision making, product roadmaps, and execution risk on our road to connecting one billion users.

**You Will: **

• Develop, build, and support large scale forecasting systems for business growth
• Develop, build, and support modeling of long-term user outcomes
• Design and implement batch prediction infrastructure that ensures high-levels of accuracy, provides explainability, and quantifies uncertainty
• Collaborate with data science and product partners to unlock causal understanding of our business growth and to develop scalable solution for measuring ecosystem health
• Model and promote a high bar for technical excellence in the broader data science and ML community.
• Communicate strategic findings to influence company and team-level roadmaps
• Partner with Data Engineering and Data Platform teams to ensure model development, reporting, and monitoring systems are built in a reliable and robust way.

**You Have: **

• 5+ years of industry experience in prototyping and building scalable machine learning solutions.
• Experience building scalable and robust ETL data and ML pipelines with complex upstream dependencies and accountability for downstream consumers
• Experience with time series modeling in practice and theory. Experience with foundational time series models (i.e. transformer based) and fine tuning frameworks.
• Demonstrated ability to lead project areas from scratch, and break product requirements into iterative deliverable stages.
• Strong communication skills to connect model outputs to company-level strategy and to integrate horizontal solutions into vertical team operations and systems.
• An Advanced Degree (MSc or PhD) or equivalent degree in Statistics, Economics, Operations Research, Computer Science, Applied Math, Physics, Engineering, or other quantitative fields.