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Render is a modern cloud platform for developers building AI-native, full-stack applications. The company has raised $260M in funding (Series C in February 2026) and is trusted by over 7 million developers worldwide.
You'll join the Data team as a Staff Data Scientist, serving as a strategic analytics partner across the organization. This is a high-impact individual contributor role where you'll work closely with leaders and teams in Product, Growth, Go-to-Market, Finance, and Engineering to tackle increasingly complex questions about developer discovery and adoption, engagement and retention, and business growth opportunities.
Key responsibilities include:
- Partner with cross-functional leaders to identify high-impact questions, frame decisions, and define success metrics
- Develop KPIs and measurement frameworks across acquisition, activation, adoption, engagement, retention, conversion, expansion, and customer outcomes
- Surface patterns in user and customer behavior to identify opportunities, diagnose friction, and inform investment priorities
- Design and analyze experiments, develop guardrail metrics, and guide teams on appropriate analytical approaches
- Build and maintain dbt models and semantic layers in partnership with Analytics Engineering to create reliable datasets
- Establish analytical best practices and mentor cross-functional partners on measurement, experimentation, and data literacy
- Explore how AI-assisted tools can enhance analytics speed and accessibility
You'll help shape Render's analytics culture and measurement frameworks while maintaining high standards for accuracy and analytical rigor.
REQUIREMENTS:
- 7+ years of analytics experience with a track record of shaping strategy and influencing decisions across complex problem spaces
- Strong business and product judgment; ability to translate ambiguous questions into rigorous analysis
- Experience defining and using metrics across product, growth, customer, Go-to-Market, Finance, or related domains
- Strong SQL skills; ability to write complex, efficient queries and independently explore large datasets
- Experience with experimentation, statistical analysis, or rigorous evaluation methods to understand impact
- Expertise in statistical methods beyond A/B testing (causal inference, cohort/survival analysis, time-series analysis)
- Experience with modern analytics tooling (Metabase, Mixpanel, Looker, Amplitude, or similar)
- Experience with dbt and modern data stacks (BigQuery, Segment) and version control (Git)
- Track record of influencing cross-functional teams and senior leaders without direct authority
- Excellent communication skills; ability to translate complex analysis into clear narratives
- Experience using AI-assisted coding or analytics tools (Codex, Cursor, Claude Code)
NICE-TO-HAVES:
- Experience with developer-focused, product-led, sales-led, or usage-based businesses
- Knowledge of cloud infrastructure, PaaS, developer tooling, or technically complex products
- Experience analyzing multi-product or multi-segment businesses
