Product Data Scientist

About AvePoint: 

Beyond Secure. AvePoint is the global leader in data security, governance, and resilience, going beyond traditional solutions to ensure a robust data foundation and enable organizations everywhere to collaborate with confidence. Over 25,000 customers worldwide rely on the AvePoint Confidence Platform to prepare, secure, and optimize their critical data across Microsoft, Google, Salesforce, and other collaboration environments. AvePoint’s global channel partner program includes approximately 5,000 managed service providers, value-added resellers, and systems integrators, with our solutions available in more than 100 cloud marketplaces. To learn more, visit www.avepoint.com.

At AvePoint, we are committed to investing in our people. Agility, passion and teamwork set us up to do our best work and foster a culture where you are empowered to craft your career, make an impact, and own (y)our future. Unleash the power of you!

About the role:

We are seeking a Product Data Scientist to join our data analytics team and drive data-informed decisions and enabling product-led-growth for our B2B SaaS products. This role will focus on analyzing product performance, understanding customer behavior, and designing experiments that optimize acquisition, adoption, retention, and growth. You will work with diverse datasets including customer transactions, feedback, telemetry, and technographics, to uncover actionable insights that shape product strategy and enhance customer experience.

Key Responsibilities:

• Analyze Product Performance:
  • Evaluate commercial performance metrics across product lines, bundles, and features in different segments.
  • Enhance product-led growth metrics such as user activation rates, feature adoption, expansion revenue, and virality.
  • Identify trends, opportunities, and risks impacting revenue and adoption.
• Customer Behavior Analysis:
  • Use statistical and machine learning methods to model customer usage patterns, needs, and retention drivers.
  • Segment customers by lifecycle stage (e.g., new, activated, power users, churn risk) to inform targeted in-product experiences and drive upsell/cross-sell through personalized product journeys.
• Experimentation & Optimization:
  • Design, execute, and analyze A/B tests and other products experiments to validate hypotheses that accelerate product-led growth.
  • Develop frameworks for testing new features, pricing models, and onboarding flows.
  • Identify opportunities to enhance the product’s ability to drive growth autonomously
• Insights & Recommendations:
  • Translate complex data into clear, actionable insights for product managers, product marketing, and business stakeholders.
  • Deliver actionable insights that empower product managers to prioritize PLG initiatives, such as optimizing self-serve onboarding, driving feature discovery, and reducing friction in the user journey
  • Build dashboards that track PLG KPIs and OKRs around activation, expansion, retention, referral.
  • Customer sentiments on products and feature requests.

Required Qualifications

• Advanced degree in Data Science, Statistics, Computer Science, or related field.
• Strong proficiency in Python/R, SQL, and data visualization tools (e.g., Power BI, Tableau).
• Experience with machine learning techniques (classification, clustering, regression) and statistical modeling.
• Hands-on experience with experiment design and causal inference.
• Demonstrated experience supporting product-led growth strategies in SaaS environments, including experimentation, user segmentation, and lifecycle analytics.
• Familiarity with SaaS metrics (e.g., ARR, churn, LTV, CAC) and customer lifecycle analytics.

Preferred Qualifications

• Knowledge of telemetry and product analytics tools (e.g., Mixpanel, Amplitude, Gainsight).
• Experience working with large-scale datasets and cloud platforms (Azure, AWS, GCP).
• Strong communication skills to present insights to technical and non-technical audiences.

Impact of the Role

Your work will directly accelerate product-led growth by enabling data-driven decisions and experimentation that empower users to discover value, convert, and expand through the product experience.

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