About the RoleThe Data Scientist is a technical analytics role supporting Finance, Operations, Marketing, and Development with data and business analysis. The majority of the role is hands-on coding and analysis: writing SQL against a Snowflake data warehouse, building Python-based analytical models, and developing BI dashboards. The role covers the full spectrum from descriptive analytics (what happened) to predictive modeling (what will happen) to prescriptive analysis (what should we do about it).
A Day in the Life- Write SQL and Python to build, test, and maintain analytical datasets and pipelines in Snowflake.
- Build descriptive analytics: dashboards, KPI frameworks, and ad hoc queries that answer "what happened and why."
- Build predictive models: forecasting, segmentation, and other statistical/ML models that answer "what's likely to happen."
- Build prescriptive analysis: scenario modeling and recommendations that answer "what should we do."
- Partner with Finance, Ops, Marketing, and Development stakeholders to scope analytical questions and translate business problems into data solutions.
- Design and maintain BI dashboards (Power BI, Omni) for self-serve reporting across teams.
- Conduct exploratory data analysis to surface trends, anomalies, and root causes in business performance.
- Present findings and recommendations clearly to both technical and non-technical audiences.
What Sets You Apart- Strong hands-on coding ability in SQL and Python; comfortable building datasets and models from raw data, not just querying finished tables.
- Working knowledge of statistical and machine learning methods (regression, classification, clustering, time series forecasting) and when to apply them.
- Experience building and maintaining BI dashboards (Power BI, Looker, Tableau, or similar) for multiple business audiences.
- Ability to translate ambiguous business questions from Finance, Ops, Marketing, or Development into a defined analytical approach.
- Strong data modeling and data warehousing fundamentals (Snowflake, dbt, or similar).
- Advanced analytical and problem-solving skills, with the ability to move from data exploration to a clear recommendation.
- Ability to thrive independently in a fast-paced, dynamic environment while managing multiple priorities.
- Strong communication skills, capable of explaining technical work to non-technical stakeholders.
Education and Experience- Bachelor's degree in data science, statistics, computer science, or a related quantitative field.
- 3+ years of experience in data science, data analytics, or business analytics, including hands-on SQL/Python work and applied statistical or ML modeling.
- Experience with cloud data warehouses (Snowflake or similar) and BI tools (Power BI or similar).
- Experience supporting cross-functional business stakeholders (finance, operations, or marketing analytics) is a plus.
Benefits & Perks
We offer a comprehensive benefits package designed to support your health, well-being, financial future, and professional growth.
- Health & Wellness: Medical, Dental, Vision, HDHP with HSA, employer-paid Life Insurance, Disability, Mental Health & EAP benefits
- Financial: 401(k) with Safe-Harbor Matching and additional voluntary benefits, including pet, legal, identity theft, accident, hospital, and critical illness coverage
- Time Off: 17 days of PTO (increases with tenure), 11 paid holidays, paid parental/adoption/foster leave, plus dedicated Wellness/Mental Health and Volunteer days
- Hybrid Work: In-office Monday-Thursday and remote Fridays
- Professional Growth: Up to $500 annual professional development stipend
- Employee Perks: Weekly office breakfast, Fun Committee, DE&I Council, employee discounts, and time off to vote
Benefits are generally effective the first of the month following 30 days of employment and are subject to applicable plan terms.
*This role is not eligible for visa sponsorship* 
