buffer - Senior Data Scientist (Full Stack)
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Requirements
• You care deeply about creators, small businesses, and individuals, and are motivated by helping them succeed through better product and data-informed decisions • Deep hands-on experience with modern analytics stacks, including SQL-based data warehouses (BigQuery preferred; Snowflake or Redshift also relevant), BI tools such as Metabase, Mixpanel, Looker, or Mode, data transformation frameworks like dbt, and event tracking platforms like Segment • Strong foundation in statistical analysis and causal reasoning, with fluency in SQL and advanced experience using Python or R for analysis, modelling, and data visualization • Proven track record of owning complex, ambiguous analytical problems end-to-end, from framing and data exploration through to recommendations that influence product and business decisions • Experience designing, analyzing, and interpreting experiments, including A/B testing, incrementality, and causal analyses, with a strong sense of methodological tradeoffs • Experience building and maintaining analytical models across the full customer lifecycle, including acquisition, activation, engagement, retention, and monetization • Demonstrated ability to balance high-impact strategic work with day-to-day analytical support, while systematically reducing ad hoc requests through better tooling, documentation, and self-serve systems • Strong cross-functional partner to product managers, marketers, engineers, and designers, able to influence direction through data rather than operating as a service function • Skilled at translating complex, messy data and ambiguous questions into clear metrics, narratives, and actionable insights for a wide range of stakeholders • High degree of ownership and judgment, comfortable acting as the primary or most senior Data Scientist within a small team and shaping how data work gets done • Experience leveraging modern data and AI-assisted tools to increase analytical leverage, improve insight accessibility, and scale impact across the organization • By submitting the application, you consent to Buffer collecting and processing your personal data for recruiting purposes, find more details in our Privacy Policy.
Responsibilities
• Serve as Buffer’s primary Data Scientist, supporting product and growth teams with analysis that informs decisions and prioritization • Build and maintain behavioural and business models across acquisition, activation, engagement, retention, and monetization • Lead complex analyses and research to identify product and growth opportunities, not just validate existing ideas • Design, analyze, and interpret experiments across product and growth initiatives, including A/B tests and incrementality studies • Partner with cross-functional teams to define success metrics, evaluation frameworks, and clear decision criteria • Develop reusable datasets, models, and reporting patterns that reduce ad-hoc requests and increase self-serve capability • Help evolve Buffer’s data systems, definitions, and measurement approach as we invest in analytics product features and personalization • Use AI-assisted tools to streamline analysis, accelerate insight generation, and make data more accessible across the organization • Communicate findings through clear narratives, documentation, and recommendations that influence decisions at multiple levels • Improve the reliability of our analytics foundations through better modelling patterns, data quality checks, documentation, and clear sources of truth • Partner with engineering to strengthen the data platform over time, including clearer ownership boundaries, better observability, and fewer fragile workflows • Help shape our approach to AI-assisted analytics responsibly, including safer defaults, governance considerations, and a bias toward trusted semantic layers over free-form querying
Benefits
• $192,600 – $224,272 • Offers Equity • We strive for Buffer’s approach to salary, equity, and benefits to be: • Read more about our compensation philosophies and approach here. • Upload your resume here to autofill key application fields. • Drop your resume here! • Parsing your resume. Autofilling key fields... • or drag and drop here • What excites you about Buffer’s mission and the kind of work we do? How do you see yourself contributing to it in this role? • What problem were you trying to solve, and why did it matter? How did you approach the analysis or modelling work, and how did you partner with stakeholders to drive a decision or change? Please include context about your role, the data and tools you used, how insights were communicated, and the impact or outcomes that followed. We’re especially interested in what you learned and what you might do differently next time. • What problem would it solve, how would you approach it, and how would you know it worked? • What happened, and how did you handle it? What did you learn from it? • Optional: Tell us something you’re passionate about. This can be a serious or lighthearted topic. Please record a casual video response (4 minutes or less), and paste the link here from Loom or the video tool of your choice.
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