Data Analyst II, Customer Experience

As a Data Analyst II at Spring Health, you'll focus on delivering both custom and standard reports that communicate our platform's impact on mental health care. Your responsibilities will include collaborating with Product Managers to evolve our reporting suite, analyzing data from multiple sources, and developing impactful dashboards that convey compelling stories. You'll work closely with internal stakeholders and ensure the data provided is reliable and of high quality.

To succeed as a Data Analyst II at Spring Health, candidates should have at least 3 years of experience in data analysis, data visualization, and dashboarding tools such as Looker or Tableau. Proficiency in SQL is essential, and familiarity with R and dbt is a plus. Strong analytical skills, attention to detail, and exceptional communication skills are crucial for explaining complex data concepts to non-technical audiences.

The Data Analyst II position at Spring Health is remote, promoting a dynamic and collaborative environment that values communication among team members. While you'll primarily work from home, there is an expectation of quarterly travel for team collaboration and company events, enabling you to connect with colleagues and engage with our mission personally.

Spring Health is committed to the growth of its employees, providing up to $1,000 per year for professional development and a supportive work environment that encourages continuous learning. As a Data Analyst II, you will have opportunities to expand your skills and knowledge, which is essential for adapting to new challenges in the data analysis field.

Data Analyst II team members at Spring Health benefit from a comprehensive total rewards package, including health, dental, vision benefits starting on the first day, a generous 401(k) match, paid time off, and access to wellness programs. The company also offers a yearly allotment of no-cost visits to mental health providers within the Spring network, parental leave, and unique perks that focus on employee well-being.

In a data analysis interview, articulate your systematic approach to breaking down data sources, identifying key metrics, and determining which insights will be most valuable to stakeholders. Highlight your proficiency with SQL and data visualization tools, and provide examples of projects where your analysis significantly impacted decision-making.

To answer this question effectively, provide a specific example where you faced data quality issues, tight deadlines, or complex stakeholder requirements. Explain the steps you took to resolve the challenges, emphasizing collaboration with team members and innovative solutions you implemented to achieve the desired results.

Share your preferred data visualization tools, such as Looker, PowerBI, or Tableau, along with reasons for your choices. Discuss the features you find most beneficial for creating reports that effectively communicate insights, as well as your process for ensuring that visualizations are clear and engaging for diverse audiences.

Outline your methods for data quality assurance, including initial validation, regular audits, and checks against known benchmarks or historical data. Emphasize the importance of communication with stakeholders to clarify data definitions and requirements to ensure alignment and consistency throughout the reporting process.

In this case, choose a real-world scenario where you simplified complex data findings for a non-technical team or client. Discuss your approach to breaking down jargon, using analogies, and focusing on their business implications, helping them understand the significance of the data-driven insights.

Discuss your approach to assessing the urgency and impact of each request, and how you communicate timelines with stakeholders. You can mention using project management tools and collaborating with the team to balance workloads and deliver timely support while maintaining high-quality standards.

Describe specific techniques you use, such as statistical analysis, data visualization, or machine learning methods. Highlight your experience with tools like R or Python to analyze large datasets and extract valuable insights that inform product development and enhance customer experiences.

Mention your commitment to lifelong learning, including attending industry conferences, engaging in professional networks, and participating in online courses or webinars. Cite specific resources you follow for data analysis trends and innovations, showing that you are proactive in enhancing your skill set.

Share experiences where you implemented automation to streamline reporting processes. Explain how you identified repetitive tasks, utilized tools like dbt or Looker to enhance efficiency, and the positive outcomes that resulted from reducing manual efforts, ultimately freeing up time for more strategic analyses.

Express your enthusiasm for the role by aligning Spring Health's mission with your values. Discuss your passion for data-driven insights in enhancing mental health care, your excitement about collaborating with cross-functional teams, and your eagerness to contribute to impactful projects that improve lives.