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Tier-1 brand, metro location, mid-level generalist role, and broad cloud+ML requirements increase competition.
Data engineering and analytics skills are moderately transferable across industries despite domain-focused healthcare experience.
Explicit 5+ years and mandatory Azure, Snowflake, SQL, and ML/data engineering skills.
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Lead development and deployment of advanced machine learning and statistical models to solve complex healthcare problems.
Design and implement scalable data pipelines, ETL workflows, and data integration strategies using Snowflake and Azure Stack services.
Collaborate with global stakeholders to influence product and business strategy while mentoring the data science team and maintaining expertise in ML and healthcare analytics.
5+ years of experience building data analytics, data engineering, and machine learning solutions.
Mandatory skills: Expertise in Azure Stack services, Snowflake, SQL with dimensional modeling, and experience in Power BI or Tableau.
Bachelor of Engineering degree required.
Programming proficiency in R or Python preferred; knowledge of advanced statistical analysis, machine learning, and predictive modeling.
Experienced in leading AI research projects and applying innovative data analysis techniques in healthcare analytics.
Strong ability to convert real-world healthcare challenges into scalable data science solutions and drive data-driven decision-making.
Capable of mentoring and enhancing technical capabilities of a data science team with excellent communication skills to simplify complex technical concepts.