Data Analyst

Evlo AI; Los Angeles (CA); In loco; USD 110.000 - 170.000; Tempo pieno

Descrizione del lavoro

Evlo AI in Los Angeles is seeking a data analytics professional to turn raw operational data into actionable metrics and executive dashboards. You will own data exploration, dashboard development, and self-serve analytics infrastructure, collaborating with data engineers on warehouse modeling.

You will translate business questions into rigorous analyses using SQL, Python or R, and present findings to senior leaders. A background in analytics at a product-driven company is required.

Competenze

• 3-6 years of experience in data analytics, analytics engineering, or closely related role at a product-driven company.
• Expert-level SQL — complex joins, window functions, query optimization — with a modern cloud data warehouse.
• Hands-on experience with at least one BI platform (Looker, Tableau, Mode, or Power BI) and dashboard design for executive audiences.
• Proficiency in Python or R for analysis: pandas, statistical testing, and data manipulation at scale.
• Experience with dbt and dimensional modeling; understanding star schemas and slowly changing dimensions.
• Track record of communicating analytical findings to non-technical stakeholders and influencing product or business decisions.
• Bachelor's degree in a quantitative field or equivalent practical experience.
• Bonus: Experience with experimentation platforms and orchestration tooling.

Mansioni

• Own end-to-end business analytics: define KPIs, build metric definitions, and maintain alignment across product, growth, and operations stakeholders.
• Write complex, performant SQL against a cloud data warehouse to answer questions spanning user behavior, retention, revenue, and funnel performance.
• Build and maintain dashboards in Looker, Tableau, or Mode that leadership and cross-functional teams rely on daily.
• Develop dbt models and contribute to dimensional data modeling, working with data engineers on warehouse architecture and documentation.
• Design and execute deep-dive analyses - cohort retention, A/B test evaluation, unit economics - using Python or R, and present findings to senior stakeholders with clear recommendations.
• Improve data reliability by monitoring dashboards and pipelines, investigating anomalies, and partnering with data engineering on root-cause fixes.
• Empower self-serve analytics across the org: document metrics, build reusable datasets, and train non-technical users on tooling.

Conoscenze

SQL expertise

BI dashboard design

Python or R

dbt & dimensional modeling

Data warehousing concepts

Stakeholder communication

Formazione

Bachelor's degree in quantitative field

Strumenti

Looker

Tableau

Mode

Power BI

Descrizione del lavoro

About The Role

The role turns raw operational data into the metrics and insights that drive company decision-making - owning everything from data exploration to executive dashboards and self-serve analytics infrastructure.

About The Role

The role turns raw operational data into the metrics and insights that drive company decision-making - owning everything from data exploration to executive dashboards and self-serve analytics infrastructure.

The position sits at the intersection of analytics and engineering: writing production-quality SQL, partnering with data engineers on warehouse modeling, and translating ambiguous business questions into rigorous, reproducible analyses.

Key Responsibilities

• Own end-to-end business analytics: define KPIs, build metric definitions, and maintain alignment across product, growth, and operations stakeholders
• Write complex, performant SQL against a cloud data warehouse (Snowflake, BigQuery, or Redshift) to answer questions spanning user behavior, retention, revenue, and funnel performance
• Build and maintain dashboards in Looker, Tableau, or Mode that leadership and cross-functional teams rely on daily
• Develop dbt models and contribute to dimensional data modeling, working alongside data engineers on warehouse architecture and documentation
• Design and execute deep-dive analyses - cohort retention, A/B test evaluation, unit economics - using Python or R, and present findings to senior stakeholders with clear recommendations
• Improve data reliability by monitoring dashboards and pipelines, investigating anomalies, and partnering with data engineering on root-cause fixes
• Empower self-serve analytics across the org: document metrics, build reusable datasets, and train non-technical users on tooling

What We Are Looking For

• 3-6 years of experience in data analytics, analytics engineering, or a closely related role at a product-driven company
• Expert-level SQL - complex joins, window functions, query optimization - and proven experience with a modern cloud data warehouse
• Hands-on experience with at least one BI platform (Looker, Tableau, Mode, or Power BI) and dashboard design for executive audiences
• Proficiency in Python or R for analysis: pandas, statistical testing, and data manipulation at scale
• Experience with dbt and dimensional modeling; strong grasp of data warehousing concepts like star schemas and slowly changing dimensions
• Track record of communicating analytical findings to non-technical stakeholders and influencing product or business decisions
• Bachelor's degree in a quantitative field (statistics, economics, computer science, engineering) or equivalent practical experience
• Bonus: Experience with experimentation platforms (e.g., Statsig, Optimizely), Airflow/Dagster orchestration, or building metrics layers in Snowflake