Data Scientist, Waymark

• Education: A Master’s degree in Data Science, Computer Science, Statistics, or a related field. We are prioritizing early-career applicants for whom this would be their first data science role
• Python Proficiency: 5+ years of hands-on experience in Python, with demonstrated use of data science and machine learning libraries. This includes Python experience during academic training
• Machine Learning Application: Demonstrates academic and practical experience applying machine learning techniques, including model development, tuning, and deployment
• Portfolio of Work: Evidence of data science expertise, demonstrated through GitHub repositories or a similar portfolio of past projects
• Technical Documentation: Experience creating detailed technical specifications and documentation, including system architecture and technical requirements
• Project Leadership: Experience managing multiple data science projects, including responsibilities for technical design, execution, and testing
• Team Collaboration: Proven ability to work effectively within a small team environment, with a clear track record of fitting into and contributing to collaborative, agile teams
• As a startup, we value a proactive, flexible, go-getter approach in our team members
• You must have a demonstrated ability to run with your projects with minimal guidance, working closely with stakeholders across disciplines to craft a solution
• This role requires strong project management skills, with the ability to manage multiple projects simultaneously, prioritize tasks effectively, and make informed trade-offs between building an MVP and longer-term goals
• We are looking for someone who can create clear project plans, size work accurately, and understand how to balance immediate needs with future scalability
• Additionally, we have a highly collaborative team, so you should be team-oriented, eager to work with other data scientists, and willing to support various tasks across the broader technology development team, including engineering, product, and analytics
• These soft skills are essential to thrive in our fast-paced, cross-functional environment

Desirable

• Our 2025 data science roadmap focuses on three core projects: deploying AI in clinical workflows to maintain the quality of care for patients, expanding LLM automation to reduce administrative work for our care team members, and advancing machine learning prediction models to help target the right patients with the right interventions
• We’ll implement real-time decision-support tools to give our patient-facing teams actionable insights into patient needs and optimal interventions
• LLM automation will extend to tasks like patient intake, scheduling, follow-up, documentation, and triage, reducing manual work for healthcare staff
• Additionally, we’ll enhance existing machine learning models through complex feature development and build new models for patient-targeting and intervention-deployment tasks
• Achieving these goals requires prototyping, experimentation, peer-reviewed publication, and close collaboration with product, care quality, and engineering teams to align on business and clinical needs and scale our tools effectively within our broader application
• A core part of this role involves a strong understanding of claims data and healthcare data science modeling methods, including predictive modeling, risk stratification, and patient segmentation, to inform our models and solutions
• Document Technical Requirements for Data Science Tools: Develop clear technical specifications across multiple data science tools, detailing architecture, algorithms, and core functionalities. Engage with team members to ensure high-quality solutions and timely delivery
• Collaborate on Delivery Timelines: Work with data science and product leads to define project goals, MVP scope, and long-term enhancements. Establish and maintain organized documentation and delivery timelines to keep leadership and team members aligned on progress
• Create Thorough Technical Documentation: Produce detailed documentation on technical designs and project plans, including work sizing, prioritization, and trade-offs, providing visibility and alignment for all stakeholders, including leadership
• Hands-on Coding and Team Collaboration: Dedicate significant time to coding daily while also collaborating fluidly with data science team members. Share and understand team projects, building solutions together in a dynamic environment
• Work Independently with Strong Communication to Leadership: Manage projects independently with a proactive approach. Regularly communicate project timelines, blockers, and solution progress to leadership, ensuring alignment and transparency on key milestones and challenges
• Develop Healthcare Subject Matter Expertise: Show a strong interest in healthcare data structures, quantitative methods, and data science applications in healthcare, with a commitment to publishing insights in peer-reviewed journals
• Lead and Manage Project Efforts: Own projects from planning through execution, including project management and stakeholder alignment across product, engineering, and analytics teams. Through clear communication and cross-functional collaboration, ensure cohesive, high-quality healthcare solutions

• Our interview process includes a real-time coding and data science exam, as well as a take home exam
• To be considered for the role, you must receive >90% raw score on an exam normed to expert level proficiency (i.e. , corresponding to 10 years or more of experience in Data Science)