Responsibilities
- Translate complex business questions into clear problem statements, success metrics, and actionable quantitative solutions.
- Use an iterative approach: start with quick, decision-useful analysis, then refine based on feedback and observed impact.
- Implement and maintain reliable ML/analytics pipelines, partnering with engineering as needed to productionize and monitor.
- Contribute to delivering clear, impactful insights to stakeholders.
- Collaborate across the Product organization to operationalize data science solutions that inform strategy and optimize the user experience.
- Contribute to data science and product analytics best practices through documentation, code reviews, and knowledge sharing.
Requirements
- 0-2 years of experience in Data Science and ML Engineering
- MS in Statistics, Data Science, Computer Science, or related discipline preferred; or equivalent professional industry experience
- Experience with supervised and unsupervised learning methodologies
- Experience with data exploration, transformation, and model development, with exposure to productionizing and monitoring
- Strong data fluency: selecting the right inputs, engineering business-relevant features, and validating that findings are reliable
- Familiarity with core statistical/ML methods and model validation fundamentals
- Concise and influential communication skills for a wide variety of stakeholders
- Ability to produce clear technical documentation and stakeholder presentations
- Strong attention to detail with a penchant for data accuracy
- Must successfully pass a background check
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