GDIT is seeking a skilled Data Scientist Advisor with experience supporting federal health agencies, capable of driving data-driven decision-making through advanced analytics, machine learning, and statistical modeling. The ideal candidate will lead and contribute to a range of initiatives including health informatics, predictive analytics, and program evaluation, with responsibilities spanning data wrangling, visualization, and algorithm development to improve public health outcomes.

This role requires deep technical expertise in tools such as Python, R, SQL, and cloud-based data platforms, as well as a strong understanding of federal health data standards and compliance frameworks. Equally important are strong client-facing and communication skills to effectively translate complex data into actionable insights, manage stakeholder expectations, guide junior team members, and influence mission-critical decisions through strategic data storytelling and domain knowledge.

**This role is hybrid with 2-3 days a week onsite. Must be within commuting distance to Falls Church, VA or Gaithersburg, MD.

Essential Functions & Responsibilities

Provide expert consultation in data science, machine learning, and analytics to support federal health initiatives.Curate, manage, integrate, analyze, and visualize large and complex datasets to enhance research, decision-making, and program initiatives.Develop predictive analytics, forecasting models, and data-driven solutions to address public health challenges.Design and implement scalable data storage, integration, and governance solutions while ensuring compliance with industry best practices and regulations.Build and manage databases, computational tools, and automation processes to streamline data analysis, surveillance, and public health initiatives.Stay ahead of emerging trends in AI, machine learning, and data science, sharing best practices and mentoring junior professionals.Collaborate with stakeholders on research publications, conference presentations, and data-driven insights to support program goals.Oversee project resources, documentation, and compliance with federal policies and performance guidelines.Strong consulting acumen to engage with federal health clients, translate business needs into data-driven solutions, manage stakeholder expectations, and deliver strategic insights that support mission outcomes.

Required Skills and Experience: 

Master’s degree with 10+ years of experience in data science, machine learning, computer science or a related fieldProven expertise in applying advanced tools and methodologies across various domains, including statistical modeling, experimental design, and the creation of publication-quality data visualizations5+ years of experience in developing and implementing machine learning techniques, including classical ML models, transformer-based models, computer vision, large language models (LLMs), and neural networks, using standard Python packages such as Scikit-Learn and Matplotlib5+ years of experience with programming and data analysis using SQL, Python, R, and Linux, as well as proficiency in Bash scripting and Jupyter Notebooks in both local and cloud-based environments3+ years of consulting experience, with a demonstrated ability to understand/grasp business needs, manage stakeholder expectations, and provide strategic direction and guidance on emerging AI technology trendsEligibility for Public Trust Clearance, with the ability to obtain and maintain HHS/HRSA Suitability background investigation

Desired Skills and Experience:

5+ years of experience as a Data Scientist or in a similar role, with a strong track record in data architecture and machine learning.Experience developing statistical models and implementing machine learning algorithms, with a strong understanding of forecasting models and their real-world applications to derive actionable insights.Strong expertise in machine learning, including transformer-based models, computer vision, and large language models (LLMs) on AWS and Azure.Hands-on experience with data integration tools and ETL (Extract, Transform, Load) processes. Expertise in in building data pipelines and automating reporting workflows.Proficiency in SQL, Python, and R for data analysis and model development.Experience with data visualization tools such as Tableau or Power BI for deriving and communicating business insights.Strong problem-solving, communication, and leadership skills, with the ability to collaborate across teams and stakeholders.Ability to work independently, manage multiple projects simultaneously, and take ownership of tasks from ideation to execution.Proficiency in writing queries, working with engineering teams to source, transform, and analyze data effectively.Ability to formulate business-driven questions and develop data-driven solutions.Experience evaluating system performance and reverse engineering application business logic to optimize data processes.Programming proficiency in at least one of the following: Java, Python, C, or C++.

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