Senior Data Scientist

• Full Stack

🕒 2 days ago

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51 - 200 employees

Founded 2010

💰 Venture Round - Buffer on 2017-07

Buffer is a SaaS social media management platform that helps creators, small businesses, agencies, and nonprofits plan, create, schedule, publish, engage, and analyze content across multiple social channels. It offers content creation tools (including an AI assistant), collaborative workflows and approvals, community engagement features, analytics and reporting, and a customizable link-in-bio Start Page. Buffer integrates with major social platforms such as Instagram, Facebook, X, TikTok, LinkedIn, Pinterest, YouTube, Mastodon, Bluesky, and Threads to streamline publishing and grow audiences.

📋 Description

• 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

🎯 Requirements

• Significant experience as a Data Scientist (or equivalent) in a SaaS or product-led growth (PLG) environment, with a strong understanding of SaaS metrics, growth loops, and monetization dynamics • 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 deg, 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 D