Machine Learning Engineer

About Us:
Join a dynamic and innovative team dedicated to excellence in healthcare reimbursement. At Titan, we are committed to ensuring accurate and timely payments, fostering a collaborative environment where your skills will directly impact our mission of identifying underpayment patterns to maximize revenue recovery for our clients.

Job Summary
Under the direction of the Head of Technology, the Machine Learning Engineer will be responsible for designing, developing, and optimizing machine learning models with a specific focus on healthcare data. This role requires advanced Python programming skills, expertise in machine learning techniques, and an understanding of healthcare-related data structures. Experience with FHIR is preferred, though not mandatory. Experience with healthcare data is required; familiarity and/or experience with HL7 formats (835, 837, FHIR) is preferred. The successful candidate will work collaboratively with engineering team members to develop and deploy data-driven solutions that ultimately serve to enhance patient care, operational efficiency, and improvements for our clients delivering and supporting care.

Essential Job Duties/Responsibilities

• Develop and deploy machine learning models that leverage healthcare data in collaboration with product development.
• Build, test, and maintain scalable data pipelines that feed into machine learning models, transforming raw data into structured datasets ready for analysis.
• Collaborate within Agile teams to design, implement, and support technical solutions, using a full-stack approach to integrate machine learning operations seamlessly within our applications.
• Support the adoption of machine learning frameworks in a HIPAA and HITRUST-compliant environment, ensuring robust data privacy and security.
• Optimize models for performance, accuracy, and efficiency, using Python and machine learning libraries (e.g., TensorFlow, PyTorch, Scikit-Learn).
• Work with cross-functional teams, including product managers, data scientists, software engineers, and compliance officers, to translate complex healthcare needs into technical specifications.
• Identify and resolve issues with model performance, code reliability, and system integration to ensure high-quality outputs.
• Maintain documentation for machine learning models, ensuring that both technical and non-technical stakeholders have clarity on model functionality and outputs.
• Stay up-to-date with advancements in machine learning, healthcare data standards (such as FHIR), and relevant technologies to continually improve model capabilities and performance.
• Cultivate productive relationships across teams and external partners, contributing positively to a collaborative workplace culture.
• Uphold compliance and privacy standards with a focus on protecting patient data and supporting organizational values.

Minimum Qualifications

• Bachelor’s or Master’s Degree in Computer Science, Data Science, Mathematics, or a related field (or equivalent work experience).
• Advanced proficiency in Python for machine learning, including experience with machine learning libraries (e.g., TensorFlow, PyTorch, Scikit-Learn).
• Experience with healthcare-related data structures and frameworks (e.g., FHIR, HL7, ICD-10, CPT) is preferred.
• Knowledge of Agile methodologies and ability to work effectively in Agile teams.
• Proven ability to work in HIPAA, HITRUST, or similar compliance-driven environments.
• Excellent problem-solving, analytical, and critical thinking skills with attention to detail.
• Effective communication skills, both oral and written, with the ability to explain complex technical concepts to non-technical stakeholders.
• Experience in the MS Azure stack, and data engineering tools (e.g., Azure Data Factory) is preferred