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Tier-1 brand, popular mid-level Data Engineer title, metro location, and common 3–6 year band increase candidate competition.
Core data engineering skills are transferable but healthcare-focused ML responsibilities raise domain specificity to medium.
Explicit 5+ years plus mandatory Snowflake, Azure, SQL, dimensional modeling, and ML skills increase screening rigor.
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Lead development and deployment of advanced machine learning and statistical models to address complex healthcare problems.
Design and implement scalable data pipelines and ETL workflows integrating with Snowflake/Data Lake and Azure Stack platforms.
Collaborate with global stakeholders to influence product and business strategy and mentor data science team members.
5+ years of hands-on experience in data analytics, data engineering, and machine learning solutions.
Bachelor of Engineering degree.
Proficient in SQL with deep knowledge of dimensional modeling.
Strong expertise with Azure Stack services and Snowflake; experience with Power BI or Tableau for dashboard creation.
Experienced with healthcare domain challenges and converting them into scalable data science solutions.
Capable of leading AI research projects and implementing best practices in modeling and analytical rigor.
Skilled in Python or R programming, advanced machine learning, and deep learning techniques with ability to communicate complex concepts effectively.