Job Overview
We are seeking a highly motivated and experienced Staff Data Scientist to join our Customer Success Analytics Team. In this role, you’ll drive data-driven strategies that optimize both human-assisted support experiences and the broader end-to-end customer journey. By partnering with cross-functional teams, you’ll deliver insights that enhance service design, improve operational efficiency, and elevate overall customer satisfaction. This is a unique opportunity to make a meaningful impact on both support experiences and strategic customer initiatives. If you’re passionate about shaping the future of customer success through data, we’d love to hear from you!
Responsibilities
- Define KPIs and Success Metrics: Establish key business indicators for projects, ensuring alignment with company objectives and clear measures of success.
- Strategic Recommendations: Provide actionable recommendations using diverse data sets and business knowledge, even when complete data is unavailable, to support strategic decisions.
- Data Visualizations: Translate complex data into clear, accessible visualizations that help stakeholders understand key insights and make informed decisions.
- Experimentation & A/B Testing: Design, execute, and analyze A/B tests and other experiments using a hypothesis-driven approach. Provide insights and recommendations based on test outcomes to optimize business strategies.
- Predictive Analytics & Modeling: Develop predictive models and methodologies to uncover growth opportunities and support long-term business planning.
- Enable Self-Serve Analytics: Define and implement standardized metrics, reports, and dashboards. Work with Data Engineering to ensure data quality and enhance real-time analytic capabilities.
- AI/GenAI Integration: Collaborate with AI teams to integrate AI/GenAI solutions into business processes, enhancing efficiency and innovation.
- Cross-Functional Collaboration: Partner with product, digital and customer support teams to identify opportunities, create data-driven strategies, and influence decision-making.
- Leadership & Ownership: Demonstrates boundaryless leadership and extreme accountability - proactively drives outcomes across teams and leads with influence, not authority.
- Stay Current with Industry Trends: Keep up with evolving trends and advancements in data analytics to drive innovation and continuously improve business processes.
Qualifications
- 8+ years of experience working with product analytics, web analytics, customer care analytics, or other customer experience analytics
- Advanced proficiency in SQL, “big data” technologies (e.g., Redshift, Spark, Hive, BigQuery), and BI tools (e.g., Tableau, Qlik, Dash). Qlik certification is a big plus
- Strong programming skills in Python or R; experience building ML and GenAI models, including automation and custom implementations
- Deep expertise in experimentation design (A/B/n, bandits, painted-door) and causal inference (Propensity Score, DiD, Synthetic Control) with a strategic understanding of their application
- Understanding of AI-native architectures and GenAI platforms; able to assess implications for data, testing, and behavior
- Strong business acumen and the ability to translate business strategy into testable hypotheses and learning agendas
- Strong data storytelling skills, with a proven ability to rapidly construct impactful visualization, communicate insights and influence leadership
- Excellent communication and interpersonal skills, with a proven ability to build trust and collaborate seamlessly across technical, business, and cross-functional teams.
- Comfortable working in a fast-paced environment and have flexibility to shift priorities when needed
- Bachelor’s degree in Engineering, Data Science, Statistics, Mathematics, Computer Science, Economics or related quantitative field; Master’s Degree preferred
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