Senior Data Scientist
About The Position
The Senior Data Scientist collaborates with Product Managers, Engineers, and Analysts to scope and deliver data science opportunities. The role owns the full data science lifecycle, from working with data in the warehouse through building and deploying models, analyzing experiment results, and quantifying model impact. Data scientists write the code for production models, with platform support from software engineers and no handoffs. The ideal candidate is technically skilled, practical, and impact-oriented, favoring simple solutions that can be continuously improved. Strong product and business sense, analytical problem framing, and the ability to build trust and shared understanding with stakeholders are important to reducing ambiguity and delivering effective business solutions. The position may be performed remotely across the US, or in a hybrid setup for employees near Austin, Texas. The company is currently unable to hire in Massachusetts.
Requirements
- At least 5 years of experience in a technical data role, including at least 3 years of hands-on experience building machine learning or statistical models.
- A strong mathematical foundation and knowledge of machine learning and statistical methods, such as regression, classification, clustering, and experimental design.
- A solid software engineering foundation and strong proficiency in core Python and the Python data ecosystem, such as sklearn and pandas or polars.
- Comfort owning production models, including CI/CD, testing, orchestration, monitoring, and retraining.
- Strong ownership, communication, and collaboration skills, and dedication to continuous improvement.
- Strong product and business sense, practical problem-solving, and the ability to frame and answer questions analytically.
Nice To Haves
- An MS or PhD in a quantitative field; not required.
- Experience mentoring junior data scientists.
- Experience modeling customer or human behavior in a B2C context.
- Experience building machine learning for auction, bidding, or real-time allocation systems.
- Experience designing and interpreting causal measurement, including experiments, quasi-experimental methods, incrementality testing, geo tests, or MMM.
- Experience with reinforcement learning in production, especially contextual bandits, live-traffic exploration policies, off-policy evaluation, and delayed reward attribution.
- Experience building machine learning platforms.
Responsibilities
- Build machine learning models to personalize the product and connect users with policies that fit their needs.
- Work with cross-functional stakeholders to understand business needs and develop machine-learning-based solutions.
- Analyze product data, design experiments, and drive the collection and integration of new data sources.
- Write clean, maintainable production code to operationalize models using software engineering best practices.
- Perform peer code reviews, mentor other data scientists, and drive continuous improvement in the platform and practices.
- Own the data science lifecycle, including data wrangling, model building and deployment, experiment analysis, and quantifying model impact.
Benefits
- Competitive compensation and stock option offering.
- Health, dental, vision, and disability coverages.
- HSA offering with employer contribution.
- 401(k) plan with employer match.
- Unlimited paid time off, with a three-week minimum that the company tracks.
- Paid parental leave program.
- Wellness perk of $100 per month.
- Pet adoption reimbursement of $300 per year.
- Learning and development opportunities.
- Employee Resource Groups that employees can join, participate in, or create.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
