Director of Data Science & Software Development

ImagineSoftware•Charlotte, NC

1d•Remote

About The Position

Technology Partners, LLC is hiring a Director of Data Science & Software Development to lead software development and machine learning initiatives for the RadNav platform. The role analyzes user requirements, business needs, healthcare data workflows, and product objectives to design, develop, implement, and enhance software applications and machine learning-driven functionality. The position leads software architecture and development, including APIs, microservices, technical specifications, and application frameworks, as well as the design, evaluation, and deployment of machine learning, artificial intelligence, and natural language processing solutions using statistical modeling, deep learning, and large-scale healthcare datasets. It also oversees model training and evaluation, production deployment and monitoring, scalable data science pipelines, MLOps infrastructure, databases, cloud infrastructure, and system integrations. The Director evaluates and improves existing software and machine learning systems, establishes engineering standards, performs code reviews, provides technical guidance, maintains technical documentation, researches emerging technologies, consults with clients and stakeholders, and coordinates development and implementation activities. The position may be performed remotely anywhere in the United States.

Requirements

Bachelor’s degree in computer science, bioengineering, or a related field.
At least 36 months of experience as a data scientist or in a related role.
Three years of prior experience with Python programming, including machine learning and data processing frameworks.
Three years of prior experience with React JS, JavaScript, and Django-based software development.
Three years of prior experience with MySQL, MongoDB, and data modeling best practices.
Three years of prior experience with AWS cloud services and distributed computing environments.
Three years of prior experience with MLOps pipelines, including model versioning, automated deployment, monitoring, and lifecycle management.
Three years of prior experience with software architecture, API design, and microservices-based application development.

Responsibilities

Analyze user requirements, business needs, healthcare data workflows, and product objectives to design, develop, implement, and enhance software applications and machine learning-driven functionality for the RadNav platform.
Lead the design and development of software architecture, APIs, microservices, technical specifications, and application frameworks for scalable enterprise software solutions.
Lead the design, development, evaluation, and deployment of machine learning, artificial intelligence, and natural language processing solutions using statistical modeling, deep learning techniques, and large-scale healthcare datasets.
Develop, modify, test, review, and maintain application code using Python, JavaScript, React, and related technologies.
Design and oversee model training, validation, tuning, benchmarking, and evaluation methodologies to improve model performance, scalability, and accuracy.
Design, develop, and optimize database structures, data models, cloud infrastructure, and system integrations using MongoDB, MySQL, AWS, and related technologies.
Design software solutions to operationalize machine learning in production applications, including model deployment, monitoring, scalability, integration, and continuous improvement of AI-enabled features.
Develop and maintain scalable data science pipelines, data processing workflows, and MLOps infrastructure for machine learning model ingestion, transformation, deployment, monitoring, and lifecycle management.
Evaluate existing software systems and machine learning solutions, identify technical deficiencies, troubleshoot complex issues, and implement improvements to functionality, reliability, scalability, and user experience.
Collaborate with software engineers, data scientists, and technical stakeholders to define requirements, develop technical solutions, and support product roadmap initiatives.
Perform code reviews, establish software development and machine learning engineering standards, and provide technical guidance on architecture, testing, deployment, and development practices.
Develop and maintain technical documentation, including architecture documents, machine learning design specifications, data pipeline documentation, integration requirements, testing procedures, and deployment documentation.
Research, evaluate, and implement emerging machine learning methodologies, artificial intelligence technologies, software frameworks, and cloud solutions.
Consult with enterprise clients and internal stakeholders to analyze business requirements, identify software and machine learning opportunities, and recommend technical solutions.
Coordinate technical development activities and project implementation efforts to support delivery of software releases, machine learning enhancements, and product improvements.