Senior Data Analyst

We are on a mission to revolutionize mental health care through the power of data. As a Senior Data Analyst, you will play a critical role in transforming how mental health insights are generated, understood, and applied. By analyzing data from diverse sources, you will help shape personalized, evidence-based mental health solutions and contribute to making care more accessible, effective, and impactful for individuals around the globe.

• Data Analysis & Insights:
  • Analyze large, complex datasets to identify trends, patterns, and actionable insights that inform mental health interventions and strategies.
  • Develop and present data-driven recommendations to enhance mental health care delivery.
• Machine Learning Models:
  • Collaborate with data scientists and engineers to design, build, and deploy machine learning models for predictive and prescriptive analytics.
  • Support the development of algorithms to identify patterns in mental health data and optimize care pathways.
• Reporting & Visualization:
  • Build and maintain dashboards and reports using tools like Tableau, Power BI, or similar to track mental health outcomes and initiatives.
  • Provide real-time updates and performance tracking for key health and wellness metrics.
• Collaboration:
  • Partner with cross-functional teams (e.g., Product, Clinical, Engineering, Revenue) to understand data needs and deliver actionable insights.
  • Act as a mentor to junior analysts, guiding their professional development and enhancing analytical capabilities.
• Data Management:
  • Clean, preprocess, and structure data for analysis, ensuring accuracy and usability.
  • Ensure data quality and consistency across all reporting systems while adhering to privacy and security standards in health care data.
• Advanced Analytics:
  • Strong ability to interpret data and present findings in a clear, actionable manner.
  • Experience with predictive modeling, statistical techniques, and machine learning applications.
  • Conduct statistical analysis, predictive modeling, and hypothesis testing to evaluate mental health program outcomes.
  • Design and analyze A/B tests to support the optimization of mental health tools and resources.