Senior Data Scientist II driving AI for Analytics at Instacart. Utilizing data to enhance product features and collaborating with cross - functional teams.
About the role
- Senior Data Scientist working with Buffer to enhance data utilization for product and growth strategies. Collaborating across teams to drive insights and improve decision-making.
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
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 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
- Nice to have (strong plus): Experience in an analytics engineering style role (dbt-first modelling, metric layers, curated datasets, data quality testing)
- Familiarity with data orchestration and observability concepts (even if you have not owned them end-to-end)
- Experience working with privacy, governance, and access controls in analytical environments
- Practical experience using LLM tools for analysis in a way that is secure and auditable (for example: working only on approved datasets, avoiding sensitive fields, documenting assumptions)
Benefits
- Offers Equity
Job title
Job type
Experience level
Salary
Degree requirement
No Education Requirement
Tech skills
Location requirements
Report this job
Found something wrong with the page? Please let us know by submitting a report below.
Senior Data Scientist focused on Generative AI and LLM at Manulife. Develop and implement machine learning models to solve business problems and mentor peers.
Data Scientist developing AI agents and advanced analytics solutions for Ciena. Focused on machine learning, generative AI, and delivering business value through intelligent data - driven tools.
LP
Senior Data Management Associate
LinkedIn Recruiter Post
Senior Data Management Associate role in Toronto driving data quality and governance in investment systems. 9 - month hybrid contract at $80 - 85/hr.
Data Scientist driving detection and mitigation of fraud across audio verticals on our platform. Collaborating with data scientists and ML engineers to ensure fair engagement and accuracy for users and creators.
Senior Marketing Data Scientist for Mozilla providing analytical support to marketing team's investment decisions. Measuring marketing performance and uncovering insights to enhance impact.
Senior Data Scientist developing advanced machine learning models and managing data science services. Working in a hybrid environment to address client needs and optimize business functions.
Data Science Specialist at Nasdaq analyzing financial crime data for insights. Collaborating with teams to create impactful reports and presentations for fraud detection solutions.
Data Scientist at Dropbox partnering with product, engineering, and design teams for analytics and business growth. Focusing on revenue growth, product optimization, and launching high - impact initiatives.
Senior Data Science Manager driving data science projects and mentoring teams for AI product development at Dropbox. Collaborating cross - functionally to influence product strategies and analyze impactful data - driven insights.