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MicroHealth, LLC
Vienna, VA
Summary description:
Work with the MicroHealth generative AI (GenAI) product development team to develop, enhance, and implement artificial intelligence and machine learning solutions that improve productivity and quality of output.
Job description:
Design and build predictive models using machine learning algorithms, clean and process large datasets to identify patterns and trends, and develop GenAI applications including natural language processing and computer vision systems. You will collaborate with cross-functional teams to translate business requirements into technical solutions, create GenAI applications, data visualizations and reports to communicate findings to stakeholders, optimize model performance, and ensure scalability of AI systems while staying current with emerging AI technologies and best practices.
no
Eligibility factors:
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The ideal candidate will have a degree in Data Science, Computer Science, Statistics, or related field with 3+ years of experience in machine learning and statistical modeling. You should be proficient in Python, R, SQL, and AI frameworks such as TensorFlow and PyTorch, with a strong understanding of algorithms, data structures, and statistical methods. Experience with cloud platforms like AWS, Azure, or GCP and big data tools is required, along with excellent analytical and problem-solving skills and the ability to communicate technical concepts to non-technical audiences. Preferred qualifications include experience with deep learning and neural networks, and knowledge of MLOps and model deployment practices. This position offers the opportunity to work at the forefront of AI technology while making a meaningful impact on business outcomes through data-driven insights.
Virginia
Typical pay $97K – $166K/yr
Median pay: $126K/yr
What Data Scientists typically earn in Virginia — from U.S. Bureau of Labor Statistics data (May 2025). It's the going rate for this line of work, not this employer's offer.CareerPCS publishes these benchmarks with explicit limits so they are not mistaken for an employer offer or a prediction.Read the salary methodology
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