We are seeking a highly motivated and experienced Sr. Data Scientist to join our ICS Data and Analytics Team. In this role, you’ll drive data-driven strategies to optimize Customer Success outcomes for both Mid-Market and SMB customers. If you’re passionate about shaping the future of sales technology through data, we’d love to hear from you!
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4+ years of experience working with product analytics, web analytics, customer care analytics, or other customer experience analytics
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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
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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
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Understanding of AI-native architectures and GenAI platforms; able to assess implications for data, testing, and behavior
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Strong business acumen and the ability to translate business strategy into testable hypotheses and learning agendas
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Strong data storytelling skills, with a proven ability to rapidly construct impactful visualization, communicate insights and influence leadership
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Excellent communication and interpersonal skills, with a proven ability to build trust and collaborate seamlessly across technical, business, and cross-functional teams.
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Comfortable working in a fast-paced environment and have flexibility to shift priorities when needed
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Bachelor’s degree in Engineering, Data Science, Statistics, Mathematics, Computer Science, Economics or related quantitative field; Master’s Degree preferred
Preferred:
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Strong programming skills in Python or R; experience building ML and GenAI models, including automation and custom implementations
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Experience solving growth-related problems at financial technology companies serving consumer or SMBs
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Strong analytical and modeling skills using Python (for its rich suite of statistical and modeling libraries like numpy, pandas, scikit-learn, etc.)
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Familiarity with version control software (git), and general software development
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Define KPIs and Success Metrics: Establish key business indicators for projects, ensuring alignment with company objectives and clear measures of success.
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Strategic Recommendations: Provide actionable recommendations using diverse data sets and business knowledge, even when complete data is unavailable, to support strategic decisions.
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Data Visualizations: Translate complex data into clear, accessible visualizations that help stakeholders understand key insights and make informed decisions.
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Experimentation and 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.
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Predictive Analytics and Modeling: Develop predictive models and methodologies to uncover growth opportunities and support long-term business planning.
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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.
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AI/GenAI Integration: Collaborate with AI teams to integrate AI/GenAI solutions into business processes, enhancing efficiency and innovation.
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Cross-Functional Collaboration: Partner with product, digital and customer support teams to identify opportunities, create data-driven strategies, and influence decision-making.
