Key Responsibilities:
- Write code using PyTorch and/or Tensorflow to implement, test, and operationalize deep learning models
- Collaborate with data scientists and engineers to improve deep learning models and implement business-facing solutions built on top of those models
- Take responsibility for improving code performance and quality
- Follow developments in deep learning technology to identify opportunities to improve models
Qualifications:
Data Science Technical Skills
- Bachelors or Masters (Preferred) in statistics, computer science or equivalent field with 11-13 years of relevant experience
- Strong proficiency in ML, statistics, python or R, SQL, version control (e.g., Git), health care data (e.g., claims, EHR), with emphasis on Tensorflow and Pytorch
- Ability to promote best coding practices, championing a culture of documentation/logging
- Thorough understanding of ML lifecycle, including necessary tradeoffs and associated risks
Leadership in Data Science
- Can own a project end-to-end e.g., scoping, business value estimation, ideation, dev, prod, timeline
- Collaborates and guides junior team members in completion of projects and career development
- Works cross functionally with technical (e.g., Data Science, Data Engineering) and business (e.g., clinical, marketing, pricing, business analysts) to implement solutions with measurable value
Scope and Impact
- Independently delivers clear and well-developed presentations for both technical and business audiences
- Creates data science specific project goals associated with project deliverables
- Articulates timeline changes, rationale, and goals to meet deadlines moving forward
- Values diversity, growth mindset, and improving health outcomes of our customers
Level of Influence
- Communicate with stakeholders to identify opportunities and possible solutions based on business need
- Draft project charter, timeline, and features/stories
- Influence matrix-partner leadership
