Lead advanced product analytics for a consumer product team by analyzing complex data, designing experiments, applying statistical and causal inference methods, developing metrics and reporting tools, and delivering actionable recommendations to cross-functional stakeholders and senior leadership. The role requires strong Python or R and SQL skills, product analytics experience, AI-assisted analytics proficiency, and the ability to influence product strategy.
About the Role
We're looking for a Lead Advanced Analyst to support a fast-moving consumer product team. This role sits at the intersection of data, product, and strategy - using rigorous analysis, experimentation, and statistical modeling to shape decisions that directly impact the product experience. You'll work closely with Product, Engineering, Finance, Marketing, Operations, and Data Science teams to turn complex data into clear, actionable direction, and you'll have real influence over how the product evolves.
Key Responsibilities- Work with large, complex data sets to solve challenging analytical problems using a range of statistical and quantitative methods
- Apply quantitative analysis, experimentation, data mining, and forecasting to identify trends that inform product and business decisions
- Collaborate cross-functionally with Product, Engineering, Finance, Marketing, Operations, Data Science, and Analytics Engineering teams to deliver actionable insights
- Design, execute, and analyze experiments to measure feature impact, using causal inference methods when randomized trials aren't feasible
- Design and build metrics and dimensions to monitor product and business performance
- Build reporting and analytical tools that enable stakeholders to make data-driven decisions
- Present findings and recommendations clearly to stakeholders, including senior leadership
- Stay current on industry trends and advancements in quantitative and qualitative analysis techniques
- Use AI tools to automate repetitive analytical work and support stakeholder self-service
- 6+ years of industry experience in a quantitative field (Statistics, Econometrics, Computer Science, Engineering, Mathematics, Data Science, Operations Research, or similar); Master's or PhD a plus
- Prior experience in an advanced analytics or product data science role
- Strong business acumen and strategic thinking, with the ability to conduct rigorous analysis and make sound judgment calls
- Excellent communication skills, able to explain complex concepts clearly to a range of audiences
- Proven stakeholder management skills, with the ability to collaborate and influence across functions
- Experience partnering directly with product teams on analytics strategy, experimental design, and measurement
- Experience analyzing A/B experiments and statistical data
- Experience designing and building metrics, from concept through data pipeline implementation
- Strong proficiency in Python or R, plus SQL
- Experience with AI-assisted analytics tools (e.g., Claude, ChatGPT)
- A growth-minded, agile approach with a track record of driving projects from idea to impact
- Start Date: September 15, 2026
- Duration: Through March, 2027
- Location: Remote (within the US)
- Work Schedule: Full-time, 40 hours/week (8 hours/day, 5 days/week)
- Pay Rate: $115-$128/hour + benefits (Medical, Dental, Vision, 401K)
- Positions Available: 1
- Engagement: Contract role through Maleda Tech
- Work Authorization: Must be authorized to work in the U.S. without sponsorship
Similar Jobs
Machine Learning • Payments • Security • Software • Financial Services
Owns the vision, customer focus, and product backlog for a near-real-time data product. Prioritizes work based on business value, leads backlog grooming, communicates product direction, and partners with Scrum Masters and development teams to ensure delivery aligns with client requirements and business objectives.
Top Skills:
Agile DevelopmentData VisualizationScrumUx Design
eCommerce • Fintech • Hardware • Payments • Software • Financial Services
Leads Square’s US Business Development Representative organization through managers and frontline teams. Owns pipeline generation strategy, operating cadence, performance management, forecasting, capacity planning, outbound execution, and sales technology improvements. Coaches managers, develops BDR talent, hires and retains staff, and partners with Sales, Marketing, Revenue Operations, Enablement, Analytics, and Strategy to improve funnel conversion and revenue contribution. Uses data, automation, AI, and prospecting tools to improve productivity and scale successful programs.
Top Skills:
Artificial IntelligenceAutomationCRMData EnrichmentGongLookerOutreachSales Engagement ToolsSalesforceSalesloft
eCommerce • Fintech • Hardware • Payments • Software • Financial Services
Conduct field-based, full-cycle sales across Brooklyn by prospecting local businesses, performing live demos, building partnerships, managing Salesforce pipeline, and closing Square software, hardware, and financial-services deals. The role requires extensive in-person outreach, consultative selling across restaurant, retail, and service verticals, accurate forecasting, onboarding collaboration, and consistent quota achievement.
Top Skills:
LoyaltyPayment ProcessingPayrollSalesforceSquare HardwareSquare SoftwareTime Management Technology
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine


.png)