AI/ML Solutions Architect
4 weeks ago
At UnitedHealth Group, we are committed to helping people live healthier lives and making the health system work better for everyone. Our mission is to address health disparities and improve health outcomes, especially for historically marginalized groups and those with lower incomes.
Key Responsibilities:
- Lead a team of data scientists and engineers to develop and deploy AI/ML solutions that improve health outcomes and reduce disparities.
- Collaborate with cross-functional teams to understand business requirements and translate them into actionable AI/ML projects.
- Develop and maintain a deep understanding of mathematical and statistical concepts, as well as expertise in Python, pandas, numpy, and SQL.
- Apply frameworks such as Scikit Learn, TensorFlow, and PyTorch to build and deploy machine learning models for predictive and prescriptive analytics.
- Conduct exploratory data analysis (EDA), statistical analysis, and feature engineering to derive insights and drive business decisions.
- Ensure the scalability, reliability, and efficiency of AI/ML solutions in production environments.
- Stay updated with the latest advancements in AI/ML techniques and tools, and identify opportunities to apply them to enhance existing solutions.
- Document and communicate findings, methodologies, and insights to technical and non-technical stakeholders.
Requirements:
- Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related field.
- 4+ years of experience in Data Science, AI/ML, or a similar role.
- Experience in leading a team of data scientists and engineers.
- Solid programming skills in Python, with experience in pandas, numpy, and SQL.
- Proficiency in frameworks such as Scikit Learn, TensorFlow, and PyTorch.
- Solid understanding of mathematical and statistical concepts.
- Hands-on experience in delivering production-grade AI/ML projects.
Preferred Qualifications:
- Experience with Big Data technologies (PySpark, Hadoop) and data streaming tools (Kafka, etc.).
- Familiarity with the US Healthcare domain.
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