Senior Data Scientist

Overview

Job Description

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

Required Skills

• - 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 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

Benefits

• - Competitive salary
• - Work remotely
• - 4-Day workweeks
• - Health insurance
• - Home office setup
• - Growth mindset fund
• - New laptop
• - Unlimited free books
• - AI tools stipend
• - Flexible time off
• - Savings plan with 3% company match
• - Profit sharing
• - 16 weeks of family leave for all parents, fully paid
• - Family support fund
• - Working smarter stipend
• - Sabbaticals