Staff Security Machine Learning Engineer

Cyber Defense within CVS Health is seeking a well experienced Staff Machine Learning Engineer to join and technically lead our growing team. Staff Machine Learning Engineer will be responsible for developing and deploying security specific machine learning solutions following CVS Health specific business and technology requirements. Additionally, this Staff Machine Learning Engineer will help to define, drive and deliver all aspects of the data science product development lifecycle, from solution architecting, programming, testing, implementation, delivery of data science analytics products.

What We Expect of You:

• Drives the development and implementation of advanced machine learning models and algorithms to solve complex healthcare problems, leveraging techniques such as predictive modeling, deep learning, and natural language processing.
• Collaborates with multiple departments, including data scientists, clinicians, and Information Technology (IT) professionals, to understand business requirements, define machine learning projects, and prioritize initiatives based on strategic objectives.
• Interfaces with stakeholders to define performance metrics and evaluation methodologies for machine learning models, contributing to rigorous testing, validation, and performance monitoring of models to ensure accuracy and reliability.
• Designs and implements scalable and efficient machine learning systems, including data pipelines, preprocessing, feature engineering, and model training, ensuring the quality and integrity of healthcare data used for analysis.
• Advises on the optimization and improvement of data pipelines, model training processes, and infrastructure to enhance efficiency, scalability, and performance of machine learning solutions.
• Consults on and presents technical findings, insights, and recommendations to both technical and non-technical stakeholders, contributing to the dissemination and application of machine learning insights in the healthcare industry.
• Ensures compliance with data privacy regulations, ethical guidelines, and industry standards in machine learning engineering, supporting the development of protocols and practices for model interpretability, fairness, and transparency.
• Manages team performance through regular, timely feedback as well as the formal performance review process to ensure delivery of exceptional services and engagement, motivation, and team development.
• Stays up-to-date with the latest advancements in machine learning and related technologies, continuously exploring and evaluating new algorithms and methodologies to enhance machine learning capabilities in healthcare applications.

REQUIRED QUALIFICATIONS

• 7+ years of experience in machine learning, statistical analysis, security, and network data to model risk-driven models of workforce behavior and provide context to security analysts to drive business decisions.
• 7+ years of programming experience in Python and experience with machine learning libraries such as scikit-learn, TensorFlow, and PyTorch.
• 7+ years' experience with Gen AI/LLM/NLP/MLOps or similar methodologies.
• 3+ years of customer interfacing experience (internal or external), demonstrating excellent ability to communicate technical ideas and results to non-technical audiences.
• 5+ year(s) of soliciting complex requirements and managing relationships with key stakeholders
• 5+ year(s) of experience independently managing deliverables

PREFERRED QUALIFICATIONS

• Experience developing computational methods and algorithms.
• Experience in software development and expertise in developing and applying data science methods to anomaly detection and/or times series problems.
• Experience in Cloud computing environment.
• Master’s degree in data science, Mathematics, Statics

EDUCATION

• Bachelor’s degree from accredited university or equivalent work experience (HS diploma + 4 years relevant experience)