We are looking for a Data Scientist with strong business acumen to work closely with our ML Engineering team and leadership. In this role, you will translate business questions into analytical frameworks, analyze data from our warehouse, and develop insights that directly impact strategic decision-making at the executive level.

• Partner with business stakeholders to identify opportunities for data-driven improvements
• Analyze data from our Snowflake warehouse to solve complex business problems
• Create comprehensive reports and dashboards that tell compelling business stories
• Develop predictive models that translate directly to business outcomes and ROI
• Present findings and strategic recommendations to executive leadership
• Bridge the gap between technical solutions and business applications
• Identify KPIs and metrics that align with business objectives

• 2+ years of experience in data science or business analytics
• Strong business acumen and ability to understand organizational objectives
• Excellent communication skills with experience presenting to executive audiences
• Proficiency in SQL for data analysis and querying
• Experience with data visualization tools (Tableau, Power BI, or similar)
• Demonstrated ability to translate analytical insights into business recommendations
• Experience working with stakeholders across various business functions

• Experience with Snowflake or similar data warehouses
• Knowledge of financial modeling and business metrics
• Experience with A/B testing and experimental design
• Industry-specific domain knowledge
• Background in strategy consulting, business intelligence, or similar fields

• Data Analysis: Proficiency with SQL for querying Snowflake data warehouse
• Analytics Tools: Experience with Python for data analysis (pandas, NumPy)
• Visualization: Strong skills with Tableau, Power BI, or Looker for creating executive dashboards
• Statistical Knowledge: Understanding of statistical concepts and methods for hypothesis testing
• Basic ML Understanding: Familiarity with common machine learning concepts and applications
• Collaboration Tools: Experience with Git and Jupyter Notebooks
• Nice to Have: Basic understanding of data pipelines and Kafka concepts (not required to build them)