Sr. Data Scientist - (Hybrid)

What You’ll Do 

The Data Science organization leverages predictive analytics and data science techniques to support Strive Health’s intervention programs. We build models and algorithms to help make informed decisions, enhance the quality of care, reduce costs, and ultimately improve the lives of patients with kidney disease. We aim to identify, prioritize, and implement initiatives that will impact the right patient at the right time and improve health outcomes. 

We are looking for a Sr. Data Scientist to use predictive modelling and advanced statistical analytics to support our mission. You will uncover and prioritize new/existing opportunities and make impact across the entire initiative launch cycle—from data collection design to experimentation to synthesizing actionable learnings for the end users. 

The Day to Day

Builds health economical statistical models using time series and create retroactive studies for outcome assessments. 

• Owns the planning, development, and impact assessment of ML initiatives and be hands on in building ML models using structured data and unstructured data. 
• Partners with senior leaders to define the organizational machine learning roadmap, and find opportunities to improve care and operations with ML-driven solutions. 
• Collaborates with Product and Operations to integrate ML models into clinical/operational workflows. 
• Works closely with Engineering to develop robust and scalable MLOps practices. 
• Mentors and provides technical guidance for junior data scientists. 
• Stays on top of recent developments in ML methods in recommender systems, time series forecasting, NLP, etc. 

Minimum Qualifications 

• MS/PhD in Data Science, Computer Science, Statistics, or another quantitative field. 
• 3+ years of full-time experience in building machine learning and statistical modeling. 
• 3+ years proficiency in SQL. 
• 3+ years proficiency in Python or R. 
• 1+ year experience in forecasting using time-series algorithms. 
• 2+ year experience training, deploying, and serving ML models in a cloud environment. 
• 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. 
• 1+ deep learning framework (PyTorch, TensorFlow, Keras). 
• Strong proficiency in using GitHub or Gitlab. 
• Experience with AWS Sagemaker. 
• Deep knowledge in statistics modeling. 
• Deep knowledge of the fundamentals of traditional machine learning and deep learning. 
• Strong communication and experience working with multi-functional engineering, product, and operations teams. 

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