What are the responsibilities and job description for the Data Analyst position at Evlo AI?
About The Role
The role sits at the intersection of data infrastructure and business decision-making, turning raw product, marketing, and operational data into models and dashboards that leadership actually uses.
You will partner directly with product managers, engineers, and executives to define metrics, build reliable pipelines, and answer questions where the answer changes what gets built next.
Key Responsibilities
The role sits at the intersection of data infrastructure and business decision-making, turning raw product, marketing, and operational data into models and dashboards that leadership actually uses.
You will partner directly with product managers, engineers, and executives to define metrics, build reliable pipelines, and answer questions where the answer changes what gets built next.
Key Responsibilities
- Build and maintain scalable data models in Snowflake using dbt, ensuring consistent definitions of core business metrics across the organization
- Design and develop dashboards and self-serve reporting in Tableau or Looker for product, growth, and finance stakeholders
- Write advanced SQL and Python analyses to answer questions about user behavior, retention, funnel conversion, and unit economics
- Partner with data engineers to improve pipeline reliability, data quality tests, and documentation in the modern data stack
- Define and instrument KPIs for new product launches, owning measurement from event tracking through executive reporting
- Run deep-dive analyses on experiments and A/B tests, translating statistical results into clear, actionable recommendations
- Act as an analytics point-of-contact for 2-3 business teams, proactively identifying gaps in data coverage and reporting
- 3-6 years of experience in data analytics, analytics engineering, or a comparable role at a product-driven technology company
- Expert-level SQL and strong Python skills (pandas, matplotlib/plotly) for ad hoc and repeatable analysis
- Hands-on experience with dbt and a cloud warehouse such as Snowflake, BigQuery, or Redshift
- Track record of building dashboards in Tableau, Looker, or similar BI tools used by executive audiences
- Solid grounding in statistics: experiment design, significance testing, and common analytical pitfalls
- Bachelor's degree in a quantitative field (statistics, economics, computer science, engineering) or equivalent practical experience
- Bonus: Experience with event tracking tools (Segment, Amplitude), Airflow or Dagster, and startup or high-growth environments