Senior Data Scientist, Siro

• 4-8 years of experience in data science, AI/ML, or a related field
• Proficiency in Python, SQL, and data pipeline development
• Strong background in business intelligence and data visualization tools (e.g., Looker, Metabase, Tableau)
• Experience working with structured and unstructured data in production environments
• Strong problem-solving skills with a business-focused approach
• Familiarity with LLM-driven insights is a plus but not a core requirement

Desirable

• Siro is looking for a Senior Data Scientist to play a critical role in enabling faster, more data-driven decision-making across the company.
• By ensuring that teams across Product, Engineering, Finance, Sales, and Customer Success have shared, reliable access to key data, this role will accelerate execution, improve efficiency, and unlock new strategic opportunities
• This role will be responsible for product analytics, experiment design, customer-facing insights, and business intelligence tools — helping empower teams across the company to make faster, smarter decisions at scale
• If you're excited about turning raw data into actionable insights and shaping the future of a high-growth AI-first company, this is the role for you
• Own the development and optimization of core data products — build and refine BI dashboards, reporting tools, and analytics infrastructure that drive internal and customer-facing insights
• Establish and enforce data quality standards — define governance, documentation, and best practices to ensure accuracy and trust in company-wide metrics
• Define critical data and data infrastructure needs in partnership with product and engineering
• Advance Siro’s data strategy and experimentation culture – champion data-driven decision-making, improve experimentation frameworks, and proactively surface insights that shape company strategy
• Main KPIs
• Adoption rate of customer-facing analytics dashboards (e.g., % of active customers using them)
• % of product roadmap decisions backed by quantitative data (e.g., XX% of PRDs include a quantitative data point)
• Internal team satisfaction with data access and insights