Okay, I've searched for Sr Data Scientist roles in Nashville, TN, with remote options, requiring 5+ years of experience and skills in Python and machine learning. I have found 124 positions for you.

Sure. Here's the analysis:

Job Analysis:

This Senior Data Scientist role at UnitedHealth Group, partnered through Lensa, is fundamentally about leveraging advanced data science and analytics to drive health outcomes on a massive scale. The core purpose is to evolve proof-of-concept models—particularly disease prediction frameworks that integrate AI/ML with rule-based logic—into robust, scalable products that support millions of healthcare users. This role demands not only technical mastery in programming languages like Python and SQL but also experience with big data environments such as Hadoop and cloud platforms like Azure or Snowflake. Beyond technical skills, there's a strong need for strategic thinking and innovation, as the candidate must independently prototype solutions and apply emerging analytics from other domains to healthcare. Success here involves handling complex, multi-source healthcare data, optimizing model performance for large populations, and bridging the gap between technical solutions and business impact via clear communication to diverse stakeholders. The role requires autonomy but also collaboration, working closely with data scientists, engineers, and business partners to design and deploy transformative analytics. The challenge lies in managing technical complexity, regulatory considerations implicit in healthcare data, and scaling technologies without sacrificing speed or accuracy. Ideally, this candidate is a leader not only in project execution but also in innovation, capable of driving new product development and influencing enterprise-wide analytic strategy, while thriving in a fast-evolving healthcare technology environment.

Company Analysis:

UnitedHealth Group, accessed via this position through Lensa, occupies a leading and highly influential position in the healthcare sector, marrying technology and care delivery on a global scale. It is both a stable and innovative entity focused on health optimization, reflecting a mission deeply rooted in equity, inclusivity, and transformative impact on healthcare. The partnership with Lensa, a cutting-edge career platform leveraging machine learning and user-centric talent matching, further highlights the company's commitment to innovation and tech-savviness. This suggests a culture that values data-driven decision-making, collaboration across disciplines, and a clear emphasis on diversity and inclusion. The environment is likely fast-paced and mission-driven, encouraging employees to think beyond traditional healthcare paradigms and invest in long-term societal impact. In this context, the Sr Data Scientist role is strategically positioned within a small, cross-functional team focused on scaling impactful products. Visibility to leadership and collaboration across engineering, data science, and business units is expected, with a strong orientation toward agility and continuous learning. For a candidate, aligning with the company’s values of equitable care and innovation is crucial, as is comfort with remote work and adherence to corporate policies. The role is not just a technical job but a strategic contributor to a mission that touches millions, making it a fulfilling opportunity for someone passionate about applying data science to meaningful healthcare challenges.

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

• Behavioral: Tell me about a time when you had to take an innovative approach to solve a complex data problem outside your usual skill set. How did you handle it and what was the outcome?
• Behavioral: Describe a situation where you had to communicate highly technical or complex analytics findings to a non-technical stakeholder. How did you ensure clarity and buy-in?
• Behavioral: Share an experience where you worked in a cross-functional team to scale a data product or project. What challenges did you face and how did you overcome them?
• Behavioral: Give an example of a time when you had to make a decision with incomplete or ambiguous data. What approach did you take?
• Technical: How would you approach integrating diverse healthcare data sources to build a scalable disease prediction model? What factors would you prioritize?
• Technical: Explain your experience with big data tools such as Hadoop, PySpark, or cloud platforms like Azure or Snowflake, and how you have used them to optimize data workflows or model deployment.
• Technical: Describe your process for selecting and tuning machine learning models in healthcare applications. How do you balance accuracy, interpretability, and scalability?
• Technical: What role does version control (e.g., Git) play in your data science projects, and how do you use it to maintain code quality and collaboration?
• Situational: Imagine you are tasked with improving the runtime efficiency of a machine learning model that must operate on a population scale. What steps would you take to optimize the model without sacrificing accuracy?
• Situational: How would you handle a situation where data quality issues threaten the validity of your health analytics project right before a key stakeholder presentation?
• Situational: Suppose there’s conflict between the data engineering team and data science team regarding the best approach to data structuring. How would you navigate and resolve this?
• Company Fit: What attracts you to UnitedHealth Group and its mission to improve health outcomes through technology and inclusive care?
• Company Fit: How do your professional values and experience align with UnitedHealth Group’s emphasis on equity, inclusion, and mitigating health disparities?
• Company Fit: This role offers full remote flexibility—how do you think you can be most effective working remotely within a cross-functional team?
• Questions for Interviewer: Can you share how the data science team collaborates with clinical and business stakeholders on product development here?
• Questions for Interviewer: What are the biggest challenges currently faced in scaling your AI/ML healthcare products, and how might this role address them?
• Questions for Interviewer: How does UnitedHealth Group support ongoing professional development and innovation for data scientists in this evolving healthcare landscape?