Associate Data Scientist

Position Overview

• Location Type: Remote
• Job Type: Full-time
• Salary: Not Specified

Arcadia is dedicated to happier, healthier days for all. We transform diverse data into a unified fabric for health. Our platform delivers actionable insights for our customers to advance care and research, drive strategic growth, and achieve financial success. For more information, visit arcadia.io.

Why This Role Is Important to Arcadia The Associate Data Scientist will join Arcadia’s Data Science team as a key contributor to the development of machine learning models, customer-facing deliverables, and strategic insights that support data-driven decision-making across the organization. This role reports to the Senior Director of AI and Predictive Modeling and represents a pivotal step in the evolution of Arcadia’s machine learning initiatives.

The ideal candidate will bring experience in machine learning techniques, statistical analysis, and healthcare data—particularly in value-based care models. A strong desire to continuously learn and adapt is essential. Effective communication is critical, as this role involves working cross-functionally, engaging with clients, and translating complex technical concepts for both subject matter experts and non-technical stakeholders.

What Success Looks Like

• In 3 months:
  • Gain a solid understanding of Arcadia’s data model, ingestion workflows, and machine learning deployment processes
  • Become proficient with the team’s core data tools, including Redshift, Athena, S3, SageMaker, and dbt
  • Deliver initial analytics and insights that showcase measurable value to customers
• In 6 months:
  • Establish yourself as a subject matter expert on Arcadia’s analytics platform and methodologies
  • Proactively engage with customers to understand their data needs and identify opportunities for model improvements
  • Design and develop machine learning models that generate meaningful business value and strengthen client trust in Arcadia
• In 12 months:
  • Be recognized as a go-to resource for machine learning expertise across the company
  • Lead cross-functional initiatives to enhance analytics workflows and improve data accessibility and usability
  • Drive multiple concurrent projects in collaboration with client stakeholders, consistently delivering expert guidance and impactful results

Responsibilities

• Manage and execute projects across a diverse customer portfolio, ensuring timely and high-quality deliverables
• Design and develop machine learning models for both internal initiatives and client-specific use cases
• Evaluate and monitor model performance, ensuring accuracy, reliability, and alignment with business objectives
• Present findings, methodologies, and insights to clients in a clear and compelling manner

Requirements

• Bachelor’s degree in a relevant field such as Data Science, Statistics, Computer Science, or a related discipline
• 1+ years of experience working with healthcare data, including familiarity with claims, clinical, or operational datasets
• 1+ years of demonstrated experience in developing and deploying machine learning models in real-world applications

Preferred Qualifications

• Strong analytical and problem-solving mindset, with attention to detail and a passion for data-driven decision-making
• Eagerness to learn and adapt in a fast-paced, evolving environment
• Excellent communication and collaboration skills, with the ability to work cross-functionally and engage with both technical and non-technical stakeholders
• Customer-focused, with a proactive attitude toward identifying opportunities and delivering value
• Proficiency in Python and common data science libraries (e.g., pandas, scikit-learn, NumPy, etc.)
• Experience with SQL and working with large-scale relational databases
• Familiarity with cloud-based data tools such as Redshift, Athena, S3, SageMaker, and Github
• Knowledge of machine learning model evaluation, performance tuning, and deployment best practices

What You'll Get

• The opportunity to analyze large and diverse data sets on Arcadia’s custom data platform.