About the Role
This role involves owning complex data problems, mentoring team members, and influencing product direction through deep analysis and modeling. The individual will work across functions to turn ambiguous questions into data-driven solutions.
Responsibilities
- Lead the design and implementation of machine learning models and statistical systems
- Define key metrics and build frameworks to measure product performance
- Collaborate with product and engineering teams to integrate data solutions
- Mentor junior data scientists and promote best practices
- Translate business challenges into analytical problems
- Develop and maintain data pipelines for modeling and reporting
- Present findings to technical and non-technical stakeholders
- Drive experimentation strategy including A/B testing frameworks
- Ensure data quality and integrity across systems
- Guide roadmap decisions using predictive analytics
- Own end-to-end delivery of data science projects
- Evaluate new tools and technologies for analytical workflows
- Improve personalization and recommendation systems
- Conduct deep-dive analyses to uncover user behavior patterns
- Support scalable infrastructure for data science at the organization level
Nice to Have
- PhD in a relevant discipline
- Experience scaling data science teams or functions
- Publications or presentations in data science domains
- Open-source contributions in analytics or machine learning
- Experience with real-time data systems
Benefits
- Health, dental, and vision insurance
- 401(k) retirement plan with company match
- Unlimited paid time off
- Annual home office stipend
- Remote work support allowance
- Learning and development reimbursement
- Parental leave policy
- Flexible vacation policy
- Wellness programs
- Company-wide retreats
Compensation
Competitive salary and equity package
Work Arrangement
Remote
Team
Part of a distributed engineering and data science team focused on scaling intelligent automation
Our Values
- We prioritize long-term thinking over short-term gains
- We believe in asynchronous communication and deep work
- We value transparency and documentation
- We champion inclusion and diverse perspectives
- We focus on sustainable productivity
Interview Process
- Initial screening with a hiring manager
- Technical assessment involving data modeling and analysis
- Live problem-solving session with team members
- Behavioral and values alignment discussion
- Final interview with senior leadership
Not available
