Sr. Manager, Data Science & Analytics

Sunrun•REMOTE - CA - Bay Area, CA

1d•$194,860 - $259,813

About The Position

Sunrun is seeking a highly technical, efficiency-minded Senior Manager of Data Science & Analytics to lead, reshape, and scale the company’s business intelligence and analytics functions. The role will centralize and streamline a group of 20–30 analysts currently embedded across business units, building a lean, high-performing team and raising its technical capabilities. The Senior Manager will define what analytics Sunrun should build and how those capabilities can scale. This includes partnering with Data Engineering on the centralized Data Hub, owning the enterprise SQL semantic layer, and establishing canonical metrics, governance, labeling standards, scoring frameworks, and common business definitions. The role will also replace ad hoc spreadsheets with standardized, automated data products and reporting frameworks. Working closely with Sales, Consumer Experience, Operations, and executive leaders, this leader will deliver practical analytics that improve unit economics, sales-funnel conversion, customer lifetime value, and operational performance. They will translate complex data into executive dashboards, key performance metrics, and actionable recommendations while coaching and developing the analytics team. The position calls for experience in fast-moving technology environments where data drives revenue, customer impact, and operational efficiency.

Requirements

At least 8 years of experience in data analytics, business intelligence, or applied data science.
At least 3 years in a team lead or management role overseeing analysts.
A proven track record at a Big Tech company or high-growth technology startup known for a strong data culture.
Expert-level SQL skills and deep understanding of data warehousing architecture, such as Snowflake, BigQuery, or Databricks.
Hands-on experience building or governing a semantic or SQL layer, such as with dbt or a modern metrics platform.
Proficiency in Python or R for exploratory data analysis and statistical modeling.
Deep experience with modern business intelligence platforms such as Tableau, Looker, or Sigma.
A strong focus on efficiency, lean execution, and measurable business outcomes.
Comfort operating with low structure, handling multiple responsibilities, and navigating organizational change.

Nice To Haves

Master’s degree in Computer Science, Data Analytics, Economics, Engineering, or a related quantitative field.
Experience with consumer-facing metrics, multi-channel sales funnels, or operational logistics.
Background in clean energy, IoT telemetry, or subscription business models.

Responsibilities

Centralize and streamline 20–30 analysts distributed across business units, including leading organizational restructuring to create a lean, high-performing analytics organization.
Design agile workflows, intake models, and prioritization frameworks to balance executive requests with scalable data products.
Coach and develop analytical talent, support career growth, and establish a high technical bar for business intelligence.
Partner with Data Engineering on the centralized Data Hub initiative and own the enterprise SQL semantic layer.
Establish canonical metrics, labeling standards, governance, and standardized business definitions across departments.
Design unified scoring models and frameworks across sales, consumer acquisition, and operational touchpoints.
Architect scalable reporting frameworks and move the company from ad hoc spreadsheets toward standardized, automated data products.
Partner with Sales, Consumer Experience, and Operations leaders to deliver insights that improve unit economics, sales-funnel conversion, and customer lifetime value.
Deliver practical, high-impact business analytics rather than theoretical or pure research and development data science.
Translate complex data into executive dashboards, key performance metrics, and operational recommendations.