Paradigm is rebuilding the clinical research ecosystem by enabling equitable access to trials for all patients. Our platform enhances trial efficiency and reduces the barriers to participation for healthcare providers. Incubated by ARCH Venture Partners and backed by leading healthcare and life sciences investors, Paradigm’s seamless infrastructure implemented at healthcare provider organizations, will bring potentially life-saving therapies to patients faster.
Requirements
- Strong experience in machine learning, including model training, evaluation, and deployment.
- Hands-on experience with Python, and deep knowledge of machine learning algorithms and statistical methods.
- Experience managing production-level data science infrastructure, including pipelines, deployment, and monitoring.
- Experience with GenAI/LLM-based model development and open-source frameworks for building LLM applications.
- PhD or Master’s in data science, statistics, computer science, or a related field.
- 7+ years of experience in data science or a related field, with a focus on healthcare or adjacent industries.
- 2+ years of leadership experience, with proven ability to lead data science teams and set technical direction.
Responsibilities
- Lead and mentor a team of data scientists in developing, productionizing, and monitoring ML models at scale.
- Oversee the design and deployment of algorithms, including GenAI/LLM-based models, to support trial execution activities.
- Collaborate closely with cross-functional teams, including clinicians, informaticists, engineers, and stakeholders, to align data science initiatives with business goals.
- Guide the team through the process of gathering requirements, defining model specifications, and generating training and validation datasets.
- Lead the integration of ML models into production infrastructure, collaborating with engineering teams to ensure seamless execution.
- Drive innovation in data science practices and establish a long-term technical vision for the team.
- Promote best practices in data science, ensuring high-quality code and model development through effective reviews and mentoring.
Other
- Communicate the technical and business value of data science initiatives to both technical and non-technical audiences.
- Excellent problem-solving and strategic thinking skills, with the ability to tackle complex business and technical challenges.
- Comfortable working in a mission-driven, fast-paced startup environment with high ambiguity.
- Experience with oncology and/or clinical trial data.
- Previous experience in an early-stage startup environment and enthusiasm for high-growth, dynamic, 0-1 projects.
