Staff Data Scientist, Clinical Performance
WFA Digital Insight
As the demand for data-driven insights in healthcare continues to grow, with a remarkable 25% increase in data science roles in the past year, professionals with expertise in quantitative analysis and causal inference are in high demand. Pearl Health's commitment to innovation and excellence in clinical performance makes this role particularly compelling. With the remote work landscape expanding, candidates now have more opportunities to join forward-thinking companies like Pearl Health, which values expertise in digital skills and offers a competitive benefits package. Before applying, candidates should be prepared to demonstrate their proficiency in Python, SQL, and their experience in implementing scalable data science systems.
Job Description
About the Role
The Staff Data Scientist position at Pearl Health is a key role within the Clinical Performance team, focused on designing and implementing advanced causal inference and statistical frameworks. This role is crucial for measuring and forecasting the effectiveness of Pearl's clinical products and operational services, directly contributing to the company's mission to improve healthcare outcomes. The successful candidate will lead these efforts, working closely with cross-functional teams to ensure that data-driven insights are at the forefront of Pearl's decision-making processes.The day-to-day work of a Staff Data Scientist involves a deep dive into complex data sets, applying statistical methodologies to discern trends, correlations, and causations that can inform product development and service optimization. Given the intricate nature of healthcare data, the ability to navigate 'messy' real-world data environments is essential, as is the capacity to communicate complex findings to both technical and non-technical stakeholders.
What You Will Do
- Design and implement advanced causal inference and statistical frameworks to assess the effectiveness of clinical products and services.
- Develop and maintain scalable data science systems and infrastructure within a modern cloud environment, such as AWS, Snowflake, and dbt.
- Collaborate with cross-functional teams to integrate data insights into product development and service operations.
- Conduct thorough analysis of data quality and integrity, implementing measures to ensure high standards.
- Stay updated with the latest methodologies and technologies in data science, applying this knowledge to continuously improve Pearl's analytical capabilities.
- Mentor junior team members in best practices for data analysis and interpretation.
- Present findings and recommendations to senior leadership and stakeholders.
- Participate in the development of the department's strategic goals and objectives.
- Ensure compliance with regulatory requirements and company policies regarding data privacy and security.
What We Are Looking For
- Graduate degree in a quantitative field such as Statistics, Economics, Biostatistics, or Epidemiology.
- 8+ years of experience in results-driven quantitative analysis, with a focus on healthcare or a related field.
- Proven experience in implementing causal inference methodologies in real-world data environments.
- Expert-level proficiency in Python and SQL, with experience in data manipulation, analysis, and visualization.
- Experience in building and deploying machine learning models in a production environment.
- Strong understanding of data architecture and experience with cloud-based data platforms.
- Excellent communication and collaboration skills, with the ability to work effectively with technical and non-technical teams.
Nice to Have
- Experience working in a healthcare technology company or a related industry.
- Knowledge of additional programming languages such as R or Julia.
- Familiarity with agile development methodologies and version control systems like Git.
- Certification in data science or a related field.
Benefits and Perks
- Competitive salary package.
- Discretionary performance bonus.
- Equity options.
- Comprehensive health insurance plan.
- Flexible paid time off policy.
- Remote work stipend to support home office setup and productivity.
- Opportunities for professional growth and continuous learning.
- Access to cutting-edge technologies and tools.
- Collaborative and dynamic work environment with a team of experienced professionals.
How to Stand Out
- Highlight your expertise in Python and SQL by including specific examples of projects where you applied these skills.
- Prepare to discuss your experience with causal inference and how you've applied it in previous roles, focusing on the methodologies and outcomes.
- Showcase your ability to work with complex data sets by describing a project where you had to navigate 'messy' data environments and the tools you used to manage it.
- Emphasize your understanding of cloud-based data platforms such as AWS, Snowflake, and dbt, and your experience in building scalable data science systems.
- Be ready to explain how you stay updated with the latest in data science, including any certifications, courses, or conferences that demonstrate your commitment to professional development.
- Tailor your resume and cover letter to match the requirements of the role, ensuring that your application highlights the skills and experiences that align with the job description.
- Practice presenting complex data insights in a clear and concise manner, as this is a critical skill for success in this role.
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