Lead Data Scientist - AWS Certified

Responsibilities

• Lead high-priority projects impacting the organization.
• Solve complex issues and escalate when needed.
• Mentor and train other data scientists and staff.
• Develop custom data models and algorithms.
• Build algorithms/models to improve business operations.
• Perform research, analysis, and modeling on organizational data.
• Maintain and improve existing models.
• Provide advanced data insights using predictive modeling, visualization, and analytics tools.
• Develop and test hypotheses; present clear, actionable findings.
• Collaborate with teams to resolve data issues and improve processes.
• Auxiliary in evaluating data science tools and vendors.
• Ensure compliance with organizational standards and policies.
• Support team growth by mentoring, coaching, and professional development.
• Deliver excellent service and maintain strong client relationships.

Qualifications

• Experience as a Project Lead.
• Skilled in building data sets.
• Strong presentation skills to C-level executives.
• Hands-on experience with Cogito (Required).
• AWS Certification (Required).
• Bachelor's degree in Science, Engineering, Computer Science, Mathematics, Statistics, or a related STEM field required.
• Master's degree in Data Science preferred.
• At least 7 years of experience in data science.
• PREFERRED: Experience in healthcare, hospital settings, medical informatics, healthcare IT, finance/revenue cycle data, or EHR data management.
• Strong business analysis skills (process flows, spreadsheets, modeling, etc.).
• Expertise in machine learning techniques (clustering, decision trees, neural networks, etc.).
• Advanced knowledge of statistics (regression, distributions, statistical tests, etc.).
• Strong data storytelling and requirement-gathering skills.
• Advanced knowledge of the data science project life cycle.
• Programming experience and proficiency with statistical analysis tools.
• Strong problem-solving and analytical reasoning skills.
• Experience with SQL database management tools.
• Skilled in advanced data science methods: time series forecasting, regression, A/B testing, clustering, etc.
• Strong communication skills for both technical and non-technical audiences.
• Ability to manage multiple projects independently and meet deadlines.
• Strong project management and client-handling skills.
• Ability to troubleshoot, recommend solutions, and translate complex data for stakeholders.