Staff Data Scientist
$123,000–$290,000 year
On-site · Austin, Texas, United States or Boise, Idaho, United States
Job Summary
Staff Data Scientist in Finance Systems Transformation to lead development of predictive models for finance use cases (revenue/expenses forecasting, variance analysis, scenario modeling), build production-grade analytical models in Snowflake, develop and deploy intelligent agents in a Snowflake environment, design prompts, collaborate with Finance, Data Engineering, and UX teams, translate business problems into data science solutions, build and optimize data pipelines, lead exploratory analysis, and provide technical leadership and mentorship to junior data scientists. Focus areas include budgeting, income statement, manufacturing expense data, and other finance data domains, delivering scalable decision-support solutions through agent-based workflows and robust modeling.
Required Qualifications
- Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Finance, Economics, or a related quantitative field
- 5+ years of experience in data science, machine learning, or advanced analytics roles
- Strong proficiency in Python and SQL, with hands-on experience developing, testing, and deploying predictive or statistical models on large, complex datasets
- Working knowledge of core data science and AI/ML tools, including Python libraries such as pandas, NumPy, and scikit-learn, with hands-on experience in Snowflake, Streamlit
- Experience working with Finance-related data, workflows, and business needs, including corporate finance, P&L, and manufacturing cost data, as well as forecasting, variance analysis, scenario planning, actuals-to-forecast reconciliation, or financial waterfall reporting
- Experience partnering with Finance stakeholders and cross-functional teams to deliver scalable, user-adopted solutions, and providing technical leadership or mentorship to data scientists and analysts
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