Technical lead for advanced analytics within Customer Experience: design, build, and deploy ML solutions, lead complex modeling, mentor data scientists, set modeling best practices, partner with data engineers and business leaders, and translate analytic insights for senior stakeholders.
The Senior Data Scientist serves as the technical leader for advanced analytics and data science within the Customer Experience organization. This role tackles the most complex CX and service-related analytical problems, mentors other data scientists, and partners closely with business leaders to ensure analytical work drives measurable impact.
This role balances deep hands-on technical work with thought leadership, solution design, and analytic rigor.
ResponsibilitiesAdvanced Modeling & Analytics Leadership
- Design, build, and deploy advanced analytical and machine learning solutions for CX and product support use cases
- Lead complex modeling efforts (e.g., predictive risk, outcome forecasting, driver analysis, optimization)
- Evaluate emerging AI and ML techniques for practical application within a regulated enterprise environment
Technical Direction & Mentorship
- Provide technical mentorship and review for other data scientists
- Establish best practices for modeling, experimentation, documentation, and validation
- Influence analytic standards across CX-focused data science initiatives
Partnership & Translation
- Partner with Senior Business Data Analysts & Data Engineers to translate business problems into analytically robust approaches
- Communicate complex analytical results clearly to non-technical stakeholders
- Support executive and senior leader understanding of predictive and AI-driven insights
Data & Platform Collaboration
- Collaborate with Data Engineers to ensure data pipelines, feature stores, and ML workflows are fit for purpose
- Contribute to AI-enabled self-service analytics and React-based front-end experiences where appropriate
- Master’s degree or higher in Data Science, Applied Mathematics, Statistics, Engineering, or related field (or equivalent experience)
- 9+ years of hands-on experience in data science or advanced analytics roles
- Expert proficiency in Python and strong SQL capabilities
- Proven experience building and validating ML models in enterprise environments
- Experience working with Snowflake, EDW, and complex enterprise data sources
Preferred Qualifications
- Prior experience leading analytics efforts in CX, service operations, or B2B environments
- Exposure to AI prototyping, model deployment, or ML platform integration
- Experience operating under regulatory, security, or government data constraints
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