Artificial Intelligence Engineer

Job Title / Primary Skill:

Years of Experience:

Job Location:

Must Have Skills: Python/Pyspark, ML/AIMl, SQl, Azure

Educational Qualification:

• AI Engineer 2 role to support development and deployment of new/innovative healthcare analytics algorithms solutions across multiple deployment environments.
• You will be working with multi-disciplinary project teams with industry expertise, technology skills, and functional knowledge.
• Typical activities will include requirements gathering, design, and development of software solutions and tools for machine learning (ML) development. This will involve creating ML and algorithmic solutions to process and analyze highly complex, large-scale medical data, addressing current healthcare challenges.

Requirements:

• Bachelors degree from a top-tier university with consistent outstanding academic record (degree in computer science or statistics is preferred)
• 3+ years of experience in roles focused on Machine learning tool or pipeline development to solve complex problems involving big data.
• Exceptional analytical and quantitative problem-solving skills
• Strong proficiency in Python, Pyspark and SQL
• Experience with machine learning algorithms & tool development
• Understanding of coding practices and version control software such as Git, ability to write clean and efficient code, and a good understanding of the Data Science package landscape.
• A proactive, innovative, and pragmatic approach to problem solving and the ability to think critically and independently, able to work as part of a cross-functional team.

Bonus points for:

• Knowledge of containerization technologies like docker.
• Experience in cloud technology like Azure
• Experience in automated cluster management tool like Databricks
• Experience in an informatics/data science team of a health systems/IDN, including knowledge of healthcare data, EMR integration, types of environments used for data solution development/deployment, etc.
• Knowledge of supervised machine learning methods, such as regularized regressions, ensemble tree classifiers (e.g. XGBoost), support vector machines, etc
• Good understanding of classical statistical methods, such as fitting regression models, inference testing and sampling

Responsibilities:

• Innovate analytical solutions on large scale healthcare data.
• Develop and implement algorithms using Python/Pyspark with Object Oriented methods to support scalable and reusable data processing and analysis.
• Develop innovative and effective approaches to solve problems and communicates results.