Lead Data Scientist

Compunnel, Inc.; Irving (TX); On-site; USD 100,000 - 130,000; Full time

Job summary

Compunnel, Inc. is looking for a Lead Data Scientist to spearhead data-driven strategies and insights in a healthcare context. Responsibilities include leading statistical analyses, mentoring junior data scientists, and collaborating with stakeholders to translate complex data into actionable business solutions.

The ideal applicant will boast a robust foundation in statistics, proficiency in SQL and Python, and a knack for deriving insights from complex datasets. This role offers the opportunity to work in an innovative healthcare environment and influence analytical directions.

Qualifications

• Strong background in statistics and experience with traditional statistical modeling techniques.
• Proficiency in SQL and Python for data manipulation and analysis.
• Demonstrated ability to derive insights from complex healthcare data.

Responsibilities

• Lead the development of statistical analyses to support business objectives.
• Analyze large-scale datasets to identify trends and opportunities.
• Design and implement models for decision-making.

Skills

Statistical analysis

SQL

Python programming

Data manipulation

Analytical thinking

Mentorship

Job description

We are seeking a Lead Data Scientist to drive analytical strategy, develop actionable insights, and guide data-driven decision-making within a healthcare-focused environment. This role requires a strong foundation in statistics, data analysis, and traditional modeling techniques, combined with leadership capabilities to mentor junior data scientists and influence analytical direction. The ideal candidate will be comfortable working with complex and imperfect datasets, transforming data into meaningful business and operational insights.

Key Responsibilities

• Lead the development of statistical analyses and data-driven insights to support business and operational objectives.
• Analyze complex, large-scale datasets and identify trends, patterns, and opportunities for improvement.
• Design, develop, and implement statistical models to address business challenges and support decision-making.
• Perform data extraction, transformation, validation, and analysis using SQL and Python.
• Work with structured and unstructured datasets to generate meaningful insights from complex healthcare data.
• Collaborate with business stakeholders to understand requirements and translate them into analytical solutions.
• Guide analytical strategy and provide recommendations based on data findings.
• Mentor and support junior data scientists through technical guidance, best practices, and knowledge sharing.
• Communicate analytical findings and recommendations to both technical and non-technical audiences.
• Support the development of foundational analytics capabilities and reporting frameworks.
• Evaluate opportunities to leverage machine learning and AI techniques where appropriate.
• Contribute to continuous improvement of data science methodologies, processes, and standards.

Required Qualifications

• Strong background in statistics, including experience with statistical analysis and traditional statistical modeling techniques.
• Proficiency in SQL for data extraction, transformation, and analysis.
• Strong Python programming skills for data manipulation, analytics, and model development.
• Experience working with large, complex, and imperfect datasets.
• Demonstrated ability to derive actionable insights from healthcare or similarly complex data environments.
• Experience leading analytical initiatives and influencing data-driven decision-making.
• Experience mentoring or guiding junior data scientists and analytics professionals.
• Strong analytical, critical thinking, and problem-solving skills.
• Ability to work independently and proactively drive analytical initiatives.
• Excellent communication and stakeholder management skills.

Preferred Qualifications

• Experience within healthcare, healthcare analytics, or health-related data environments.
• Familiarity with Medicaid, public health, or healthcare payer data.
• Experience working within public sector or government-related data environments.
• Exposure to machine learning and artificial intelligence techniques.
• Experience developing predictive models, forecasting models, or advanced statistical analyses.
• Experience building foundational analytics capabilities and reporting frameworks.