Laboratory Data Scientist

Access Medical Labs is one of the largest specialty diagnostic labs in the country, using 50% less blood and delivering next-day results. We offer a comprehensive test menu—from routine panels to advanced biomarkers—across blood, saliva, and urine, performing over 1,000 tests under one roof. Our ultra-automated facilities, spanning over 55,000 sq. ft., are powered by the most cutting-edge diagnostic technology and innovative lab logistics available.

Since 2003, we’ve been committed to delivering a truly exceptional client experience backed by precise and reliable testing. Every innovation we pursue is driven by one purpose: making personalized medicine more practical and accessible.

Company culture is the foundation of Access Medical Laboratories. We continue to attract mission-driven and goal-oriented professionals to our organization, where each individual and team is recognized for their accomplishments. We place a significant amount of value on teamwork and mentorship, enabling each individual to consistently grow and develop. At Access, each team member has a sense of belonging, family, and community. We enjoy coming to work every day in an environment where people feel empowered, understanding that each team member plays a significant role in providing peace of mind to patients nationally.

Job Summary: Access Medical Laboratories is seeking an innovative and business-focused Data Scientist to join our Digital Transformation team. Reporting to the Digital Transformation Manager, this role will leverage artificial intelligence (AI), machine learning (ML), predictive analytics, and data science techniques to develop solutions that improve operational efficiency, customer experience, and business performance across Operations, Finance, Commercial/Marketing, and Laboratory functions.

The ideal candidate is passionate about transforming complex business problems into scalable AI-driven solutions and enjoys partnering with cross-functional stakeholders to identify opportunities, build predictive models, deploy solutions, and measure business impact.

Job Responsibilities: Develop and implement AI and machine learning solutions that improve operational efficiency and business outcomes across multiple departments. Collaborate with business leaders to identify opportunities where AI and advanced analytics can solve operational challenges. Translate business needs into predictive models, machine learning algorithms, and actionable insights. Design, develop, validate, and deploy production-ready AI/ML models. Monitor model performance and continuously optimize solutions based on business outcomes. Analyze large, complex datasets to identify trends, patterns, and opportunities for improvement. Build dashboards and reporting tools that communicate insights to technical and non-technical stakeholders. Partner with IT, software development, laboratory operations, finance, and commercial teams to integrate AI solutions into existing workflows. Ensure data quality, governance, and compliance with healthcare data standards and organizational policies. Stay current on emerging AI technologies and recommend innovative applications that drive competitive advantage.

Initial Strategic Projects Develop predictive churn models to identify clients at risk and recommend retention strategies. Build real-time courier delivery analytics to monitor specimen collections, deliveries, and sample stability throughout transportation. Develop a \"Next Best Action\" recommendation engine for the Account Management team to improve customer engagement and retention. Create predictive inventory and labor planning models to optimize staffing levels, inventory management, and operational efficiency.

Qualifications & Skills: Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field. Master's degree preferred. 1-3 years of professional experience in Data Science, Machine Learning, Artificial Intelligence, or Advanced Analytics. Experience developing and deploying machine learning models in a production environment. Strong proficiency in Python and SQL. Experience with machine learning libraries such as Scikit-learn, TensorFlow, PyTorch, or similar frameworks. Experience working with cloud platforms such as Azure, AWS, or Google Cloud. Experience creating dashboards using Power BI, Tableau, or similar visualization tools. Strong understanding of statistical modeling, predictive analytics, and optimization techniques. Experience working within healthcare, diagnostics, biotechnology, laboratory services, or life sciences. Experience with MLOps, model deployment, and automation. Familiarity with Generative AI, Large Language Models (LLMs), and AI copilots. Experience integrating AI solutions into enterprise applications. Strong analytical and problem-solving skills. Excellent communication skills with the ability to explain technical concepts to business stakeholders. Ability to manage multiple projects in a fast-paced environment. Collaborative mindset with strong relationship-building skills. Results-oriented with a passion for innovation and continuous improvement. Ability to work independently while driving cross-functional initiatives. Strong project management and organizational skills.