Data Scientist

About Labor Pharmacy Benefit Solutions, LLC: Labor Pharmacy Benefit Solutions is a well-funded, innovative startup poised to revolutionize medication distribution through cutting-edge automation and a groundbreaking vision of national expansion. We are building a mail-order pharmacy and related products from the ground up. This is a rare opportunity to be a part of creating a technology-driven pharmacy operation from its inception.

The Opportunity: We are seeking a talented and experienced Data Scientist to join our growing technology team. You will be instrumental in building the analytical foundations of our pharmacy platform, using data to optimize automated distribution, predict patient needs, and drive operational efficiency. This is a chance to make a substantial impact on a company transforming the healthcare industry by turning complex datasets into actionable insights and production-ready machine learning models.

Responsibilities:

• Own end-to-end problem solving, from problem definition and data exploration through model development and measurement of business impact.
• Translate analytical findings into clear, actionable recommendations that influence product decisions, pricing strategies, and operational improvements.
• Design and analyze controlled experiments (A/B testing), including hypothesis development, metric definition, and statistical evaluation.
• Analyze large-scale healthcare and transactional datasets to identify trends, improve patient adherence, and enhance the user experience.
• Produce machine learning solutions, including feature engineering, model development, and training workflows, and partner with engineering teams to deploy and operate them in production.
• Work with large-scale datasets across relational and distributed data stores, optimizing access patterns for analytics and model development.
• Implement and adhere to security best practices and HIPAA compliance standards for handling sensitive Protected Health Information (PHI).
• Apply statistical analysis to evaluate model performance and support decision-making across product and operational initiatives.
• Utilize GitHub and GitHub Actions for version control and CI/CD of data science workflows.
• Contribute to model deployment strategies (e.g., batch scoring, API-based inference, or event-driven processing) in collaboration with engineering teams to support production use cases.
• Implement monitoring for model performance, data drift, and system health, with clear feedback loops for retraining and continuous improvement.
• Collaborate with engineering teams to ensure models perform reliably within production systems, with an understanding of distributed system considerations such as retries, idempotency, and failure handling.
• Adhere to Agile methodologies in a fast-paced startup environment.

Qualifications:

• 5-8 years of proven experience in data science, with a track record of deploying models into production environments.
• Strong proficiency in Python (Pandas, Scikit-learn, PyTorch, or TensorFlow) and SQL.
• Strong experience working with data and machine learning workflows in AWS (e.g., S3, compute services, messaging/streaming, and data storage), with the ability to select appropriate tools based on problem requirements.
• Strong foundation in statistical modeling and machine learning, with demonstrated experience applying models to real-world business problems and delivering measurable impact.
• Experience working with both structured (Relational) and unstructured (NoSQL) data.
• Strong understanding of security best practices, encryption, and compliance (e.g., HIPAA) for handling sensitive data.
• Strong problem-solving skills and the ability to translate business problems into mathematical frameworks.
• Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
• Experience with GitHub and GitHub Actions.
• Experience working in an Agile development environment.
• Familiarity with event-driven architectures and asynchronous processing (e.g., queues, streaming systems) is highly preferred.
• Familiarity with data visualization tools (e.g., Tableau, PowerBI, or Matplotlib/Seaborn).

Bonus Points:

• Experience in the healthcare, pharmacy, or biotech industry.
• Advanced degree (MS or PhD) in Data Science, Statistics, Computer Science, or a related field.
• Experience building MLOps capabilities including automated retraining, feature versioning, and reproducible model deployment workflows.

Job Type: Full-time, Permanent

Compensation Package:

• Yearly pay

Schedule:

• Monday to Friday

Work Location: In person

Join us at Labor Pharmacy Benefit Solutions and build the data-driven future of national pharmacy distribution!

Pay: $140,000.00 - $180,000.00 per year

Benefits:

• Dental insurance
• Health insurance
• Life insurance
• Paid time off
• Vision insurance

Application Question(s):

• Will you now or in the future require sponsorship to work in the U.S.?

Ability to Commute:

• West Jordan, UT 84081 (Required)

Work Location: In person

Salary : $140,000 - $180,000