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Global brand, mid-level ML role, metro location and broad skillset drive high applicant competition.
Core ML and data engineering skills transfer across industries, though healthcare domain experience is beneficial.
Explicit 3–5 years plus mandatory Python/SQL, ML and data-ops experience increases shortlisting strictness.
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Analyze structured and unstructured data to support reliable data retrieval for downstream applications.
Develop and implement data-driven AI/ML solutions using Python for data processing, content generation, and enrichment.
Collaborate with teams to identify data sources and contribute to backend services/APIs design for scalable data-centric applications.
Bachelor's or Master's degree in Computer Science, Data Science, AI, Software Engineering or equivalent.
3-5 years of hands-on experience in data engineering, machine learning applications, Python, and SQL-based data retrieval.
Strong SQL skills and expertise in data transformation, data profiling, and source-to-target mapping.
Familiarity with cloud technologies, preferably Microsoft Azure; experience with large data sets and relational database design.
Experienced data engineer with strong practical skills in Python and SQL focusing on enterprise data platforms and large-scale data management.
Proven ability to integrate and orchestrate data and AI/ML workflows, including backend API development and cloud-native services.
Comfortable working in collaborative global teams and supporting intelligent data retrieval and enrichment solutions in a production environment.