Senior Data Scientist 

This role requires the ability to understand and adhere to data security and confidentiality protocols and procedures while learning and evaluating emerging technologies. This role will also be soliciting and incorporating design and feature feedback from users in small, short iterations. The candidate must possess a solid understanding and have experience with systems automation platforms and technologies such as Jenkins, Terraform, and CloudFormation as well as demonstrate the ability to represent Security Platform in development and implementation of the overall global cloud enterprise architecture. 

Essential Functions 

• Partner with senior leaders to define the organizational machine learning roadmap, and find opportunities to improve care and operations with ML-driven solutions 
• Build health economical statistical models and retroactive study for outcome assessment 
• Own the planning, development, and impact assessment of ML initiatives and be hands on in building ML models using text, image, and structured data 
• Collaborate with product and operations teams to integrate ML models into clinical and operational workflows 
• Work closely with engineering and infrastructure teams to develop robust and scalable MLOps practices 
• Mentor, and provide technical guidance for an early ML team of scientists and engineers 
• Stay on top of recent developments in ML methods in the search, recommender systems, NLP, computer vision, and causal inference spaces 

Minimum Qualifications 

• MS/PhD in Data Science, Computer Science, Statistics, or another quantitative field 
• 4+ years of full-time experience in building machine learning, statistical, or analytical products 
• Internet Connectivity – Min Speeds: 3.8Mbps/3.0Mbps (up/down): Latency <60 ms 
• Business travel: <15% 

Preferred Qualifications 

• 1+ year experience at a healthcare or wellness organization 
• Strong communication and experience working with multi-functional engineering, product, and operations teams 
• Deep knowledge in statistics modeling 
• Deep knowledge of the fundamentals of traditional machine learning and deep learning 
• Experience training, deploying, and serving ML models in a cloud environment (AWS preferred) 
• Strong proficiency in Python, SQL, GitHub, scikit-learn, and at least one deep learning framework (PyTorch, TensorFlow, Keras) 

Annual Salary Range: $109,000.00-$136,000.00