Senior Data Scientist/Business Analyst

Our client is looking for a Senior Data Scientist/Business Analyst to join a fast-moving Customer Engagement and Channel Innovation team. This role is ideal for someone who thrives at the intersection of business strategy, technology, and analytics, and enjoys solving complex problems that directly impact how customers are supported, engaged, and reached through digital and omnichannel experiences. You’ll partner closely with stakeholders across business and technical functions to uncover insights from large datasets, design scalable analytics solutions, and support early-stage initiatives that improve outreach and engagement outcomes. This is a highly collaborative role with strong ownership and visibility—perfect for a self-starter who enjoys working in ambiguous environments and turning ideas into measurable results. What You’ll Do As a Senior Data Analyst, you will: • Partner with stakeholders to clarify requirements, translate business needs into analytics deliverables, and ensure shared understanding across teams • Analyze large datasets to identify trends, patterns, and actionable insights that inform strategy and operational decisions • Solve complex business problems using strong analytical reasoning and critical thinking—bringing structure to ambiguity • Own end-to-end projects, proactively identifying opportunities to improve processes, customer experiences, or outcomes • Communicate insights clearly to both technical and non-technical audiences through storytelling, visuals, and data-backed recommendations • Support cross-functional execution, including timeline coordination, deliverable tracking, meeting facilitation, and documentation • Build and implement hands-on solutions, including data pipelines, logic frameworks, segmentation approaches, and analytic outputs that enable outreach programs • Experiment and iterate—testing new ideas, tools, and approaches to drive better engagement outcomes • Contribute to analytics solutions that align with company mission, values, and regulatory standards Example Projects You May Support • Designing and improving customer onboarding journeys • Building segmentation and personalization strategies • Supporting new product and service launches • Helping early-stage initiatives move from 0 → 1 through testing, learning, and iteration • Developing analytics frameworks that improve targeted outreach across channels What This Role Is Not To set expectations clearly, this position is not: • A pure data science or advanced modeling role • Focused on deploying AI/ML models into production • A dashboard-only position with minimal stakeholder engagement What You Bring Required Qualifications • Bachelor’s degree in a quantitative field (Statistics, Math, Data Science, Computer Science, Social Sciences, or similar); Master’s preferred • Proven ability to work independently, take initiative, and drive projects forward • Strong communication skills—able to translate technical insights into business decisions • Excellent critical thinking and analytical problem-solving ability • Comfort taking on new technical challenges and building solutions hands-on • Experience using analytics tools such as SQL, PySpark, Python, R (primary skills: SQL + PySpark) • Familiarity with visualization tools such as Power BI or Tableau • Solid foundation in statistical methods and data interpretation • Strong collaboration, organization, and stakeholder management skills Preferred Qualifications • Experience in healthcare, pharmacy, insurance, or other regulated industries • Project management experience or certification (PMP, Agile/Scrum, etc.) • Exposure to cloud-based analytics platforms and large-scale data environments Who Thrives Here You’ll thrive in this role if you: • Have strong analytics skills but prefer applied, business-facing work • Enjoy ambiguity and turning early-stage ideas into structured solutions • Are comfortable operating in regulated environments • Are known as a trusted cross-functional partner and clear communicator • Come from analytics, insights, product analytics, or applied data science backgrounds