Business Data Scientist, Statistics, Platform Analytics, Google Cloud

Minimum qualifications:

• Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.
  
• 4 years of experience in a data science role using data to influence business or product decisions.
• Experience analyzing data from various sources such as product instrumentation, customer support systems, and internal operational tools.
• Experience with SQL, Python or R programming including advanced data analysis, statistical modeling, and data visualization.

Preferred qualifications:

• Ph.D. degree in a relevant quantitative field.
• Experience in causal inference techniques to measure the true impact of business actions.
• Experience in Customer Support or Support-adjacent roles.
• Ability to work cross-functionally and communicate technical findings to non-technical audiences.
• Excellent product intuition and business acumen, with experience influencing both product and business strategy.

About the job

In this role, you will be using data to solve problems and you will be a key partner to stakeholders across product, operations, and engineering, helping to drive our strategy by analyzing the entire customer journey. You will address a wide range of issues, from optimizing product features and user behavior to analyzing the customer support experience and streamlining internal processes. You will use your analytical and statistical expertise to make data-informed decisions across the board.The US base salary range for this full-time position is $166,000-$244,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Responsibilities

• Partner with product, operations, and engineering stakeholders to prioritize opportunities for improvement; collaborate with partner teams to define data requirements and build foundational datasets for key business and product initiatives.
• Drive and independently scope and analysis projects from inception to completion, defining success metrics and managing stakeholder communication along the way; design, execute, and analyze rigorous A/B experiments on product features, internal tools, and operational workflows to measure their impact.
• Apply causal inference and advanced statistical modeling to measure the impact of critical product and business initiatives and understand their key drivers.
• Manage end-to-end analyses of the user journey to identify friction points and opportunities; translate analytical findings into actionable insights and narratives for various stakeholders.
• Perform opportunity sizing for new product and business initiatives to inform the roadmap and resource allocation.