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Data Science Platform Engineer

Remote

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.

Our team hails from a broad range of disciplines and is committed to the company’s mission to create equitable access to clinical trials for any patient, anywhere. Join us, and bring your expertise, passion, creativity, and drive as we work together to realize this mission.

DO NOT SELF-SELECT OUT OF THIS ROLE BASED ON TITLE ALONE.
Data Science is an evolving, interdisciplinary field, and the perfect candidate for this role may not exist, so please apply anyway, especially if you have an interesting background or personal connection to the mission. This is a high growth role at a dynamic startup positioned at the cutting edge of clinical trials, machine learning, and software engineering. You are not expected to know everything, but you will be expected to learn quickly.

We are seeking a Data Science Platform Engineer to join our Data Science Platform Enablement (DSPE) team. In this role, you will design, build, and maintain the infrastructure and tools that enable scalable data science and machine learning solutions across our organization. You’ll work closely with cross-functional teams, including machine learning engineers, data scientists, and clinical informaticists, to support the end-to-end data science lifecycle—from data acquisition to model deployment—driving efficiency and impact in clinical trials.

What You'll Do:

  • Support the development of new product features and ML solutions, collecting technical requirements, evaluating emerging technologies, and when necessary, implementing minimal internal frameworks and libraries for codifying our task domain in composable units.
  • Develop and maintain CI/CD pipelines, ensuring reliable integration and deployment of machine learning models, shared libraries, and data processing tasks.
  • Implement and manage cloud-based solutions on AWS that support scalable data storage, compute resources, and orchestration of data science tasks.
  • Ensure compliance with data security, governance, and regulatory standards in collaboration with Data Engineering, Information Security and Developer Operations teams.
  • Monitor and troubleshoot platform-related issues, optimizing for data quality, throughput, service availability, resource allocation, and cost.
  • Support and train data scientists and machine learning engineers on platform tools and best practices, fostering collaboration and continuous learning.

Who You Are:

  • Empathetic and deeply committed to team success. You feel the weight of your team's challenges, and you rise to the occasion by taking ownership, driving solutions, and fostering collaboration to bring ideas from prototype to production.
  • 3+ years of experience working as an engineer, data scientist, or in a similar role, contributing to production-level infrastructure and tools.
  • Hands-on experience in designing, building, and maintaining data pipelines, understanding how to achieve scalability, reliability, and maintainability.
  • Excellent communication skills, with the ability to distill complex technical concepts to essential elements for both technical and non-technical audiences, with great enthusiasm.
  • Comfortable with ambiguity and capable of thriving in a mission-driven, fast-paced startup environment where innovation and adaptability are key.

Bonus: 

  • Working knowledge of the full application stack, from cloud networking to web application frontends.
  • Familiarity with data governance, compliance, and security best practices, especially in the context of healthcare or regulated industries.
  • Previous experience working  within or adjacent to the healthcare industry, oncology and/or clinical trials data.
  • Experience with our tech stack: AWS, EKS (k8s), Docker, Terraform, Kotlin, React, Python, Spark, Databricks.
  • Witch/Wizard-level command line skills
  • Demonstrated expertise in deploying and operationalizing LLMs using advanced frameworks (e.g., Hugging Face, LangChain, LlamaIndex) and MLOps tools to streamline production workflows and ensure model scalability, efficiency, and reliability in production environments

At Paradigm, we are committed to providing equal employment opportunities to all qualified individuals. We encourage and welcome candidates from all backgrounds and perspectives to apply for our open positions. We are interested in all qualified individuals and  ensure that all employment decisions are based on job-related factors such as skills, experience, and qualifications.

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