Okay, I've searched for Data Scientist roles focused on Marketing & Commercial Analytics in Hillsborough County, FL, full-time positions requiring 3+ years of experience with skills in Python and SQL, and preference for healthcare-related industries. I have found 42 positions for you.

Sure. Here's the analysis:

Job Analysis:

This Data Scientist role at Zelis is fundamentally charged with amplifying the impact of data science within the marketing and commercial domains, serving as a pivotal connector among multiple internal stakeholders—marketing, sales, product, and clients. The job’s core purpose is to transform complex, diverse datasets into actionable insights that directly influence go-to-market strategies and campaign effectiveness. This includes full ownership of the analytics lifecycle, from data ingestion and cleansing to advanced predictive modeling and visualization, all while ensuring data integrity across multiple systems. The requirement for cross-functional collaboration underscores the need to navigate varying business priorities and translate technical concepts into language business leaders readily understand, making communication skills critical alongside technical prowess. The ideal candidate will tackle challenges around data inconsistencies, scaling analytics solutions, and uncovering nuanced customer behavior through segmentation and attribution. Success in this role means not only delivering rigorous models and dashboards but also driving business growth by enabling smarter, data-informed decision-making at an enterprise level. Candidates need solid coding skills (Python, SQL), familiarity with CRM and marketing platforms, and experience with visualization tools (Power BI preferred) to create compelling stories that engage diverse audiences. While healthcare experience is a bonus, the real strategic requirement is an ability to merge deep analytics with commercial acumen and a proactive mindset to innovate continuously using emerging tools such as AI. The candidate is expected to operate with a high level of autonomy, prioritize projects effectively, and influence without direct authority, especially in a net-new role designed to broaden data science utilization within the company.

Company Analysis:

Zelis positions itself as a transformative force in the healthcare financial ecosystem, serving a vast and influential client base that includes national health plans and millions of healthcare stakeholders. This context positions the company as both a market innovator and a system integrator operating at scale, bringing technology-driven solutions to complex, fragmented financial processes in healthcare. For a data scientist in marketing and commercial analytics, this translates into a unique opportunity to impact a meaningful industry undergoing digital modernization. The company culture, as implied by its energetic and inclusive language (“Get Stuff Done”), seems fast-paced, mission-driven, and collaborative, valuing both innovation and diversity of thought. The hybrid and flexible work model suggests an adaptable environment that respects individual working styles while emphasizing team objectives. Structurally, this role is embedded within a growing analytics team but requires independence and cross-functional influence, indicating a balance between specialized expertise and broader organizational visibility. Strategically, the hire supports Zelis’s ambition to leverage data science enterprise-wide to accelerate growth and optimize business decisions—making this role critical to scaling analytical maturity and competitive advantage. The successful candidate will not only need to be technically adept but also culturally attuned to a company prioritizing impact, inclusion, and continuous improvement, all within a complex healthcare technology setting with demanding stakeholders and evolving market dynamics.

Absolutely. Here are some mock interview questions that could come up:

• Behavioral: Tell me about a time when you had to explain a complex data science concept to a non-technical stakeholder. How did you ensure they understood the key insights?
• Behavioral: Describe an instance when you identified a data quality issue that impacted your analysis. How did you address it and communicate the solution?
• Behavioral: Share an example of how you worked cross-functionally with sales or marketing teams to influence a business decision using data-driven insights.
• Behavioral: How have your diverse experiences or community involvement influenced your approach to collaboration or problem-solving in a professional setting?
• Technical: Walk me through how you would develop a predictive model to improve customer segmentation for targeted marketing campaigns.
• Technical: How do you approach building and maintaining dashboards that effectively communicate campaign performance to both technical and executive audiences?
• Technical: Explain your experience with CRM data integration and the challenges you’ve faced extracting actionable insights from such systems.
• Technical: What are your thoughts on incorporating generative AI tools into traditional data science workflows? Can you provide an example or use case?
• Situational: Imagine a marketing campaign performs below expectations, and the sales team is confused by conflicting data points. How would you investigate and resolve the situation?
• Situational: You discover inconsistencies between data sources that impact a predictive model’s accuracy just before an important executive presentation. What steps would you take?
• Situational: Suppose you are tasked with designing an analytics solution to align multiple stakeholders’ needs from marketing, product, and client services. How would you manage competing priorities?
• Company Fit: What motivates you about Zelis’s mission to modernize the healthcare financial experience, and how do you see your role contributing to that vision?
• Company Fit: Zelis emphasizes a collaborative, inclusive culture. How do you foster inclusion and diverse perspectives in your current or past teams?
• Company Fit: Given Zelis’s client base spans large health plans and providers, how would you tailor your analytics approach to meet the unique needs of such a complex industry?
• Questions for Interviewer: How does Zelis envision the evolution of the analytics team over the next 2-3 years, especially in relation to marketing and commercial functions?
• Questions for Interviewer: Can you describe examples of successful cross-functional projects led by the analytics team here, and what made them effective?
• Questions for Interviewer: What are the biggest challenges Zelis faces currently in leveraging data science for marketing and commercial growth, and how can this role make a difference?