Data Scientist

Role overview

Develop and improve statistical and machine learning models that address business problems, then work with engineering partners to make those models useful in production. The role spans experimentation, model evaluation, monitoring, and communicating findings to product and business teams. Several levels are being hired, with level determined by an applicant’s qualifications and interview performance.

Responsibilities

- Build, validate, and tune statistical and machine learning models, using sound experimental and evaluation methods. - Partner with machine learning engineers to plan for deployment and connect models to APIs, pipelines, and supporting infrastructure. - Create dashboards that track product effectiveness and surface useful findings to product and customer-facing teams. - Monitor deployed models for drift, accuracy, and reliability; recommend refinements or retraining when results change. - Turn performance findings into practical recommendations for product and business decisions, including opportunities to improve revenue or reduce costs. - Share applied machine learning practices, mentor teammates, and help develop standards for production-ready data science.

Requirements

- At least five years applying statistics and machine learning to business problems, with exposure to production machine learning workflows. - A master’s or PhD in statistics, computer science, data science, or a related field, or equivalent experience. - Strong Python skills, including experience with pandas, scikit-learn, and PyTorch or TensorFlow. - Knowledge of statistical methods, supervised and unsupervised learning, experimental design, and data visualization; Looker is specified for visualization. - Strong SQL skills and experience working with raw data and data engineering teams; Snowflake is specified. - Familiarity with AWS, APIs, model deployment, and monitoring, plus the ability to explain technical results to business and technical audiences.

Nice to have

Experience with R, Java, or Go is listed as useful. The role also calls for proactive ownership, sound problem-solving, and effective collaboration across engineering, product, and business teams.

Benefits and work setup

This is a U.S.-based remote role and does not offer work authorization sponsorship. The listing describes location-adjusted salary bands for different U.S. metro areas, along with eligible bonus and equity plans, retirement matching, medical coverage, wellness resources, flexible hours, and unlimited vacation.