Overview Goldbelt Professional Services is focused on public health, including research and development services that enhance and enlarge our customers’ operations. Our expertise is focused on the integration of scientific and technical support for Federal Civilian and DoD government partners. We are analytical, research and data-driven professionals with a team of experts ready to support our customers’ missions. Summary: Goldbelt Professional Services, LLC is seeking a Health Scientist I to work within the National Center for Immunization and Respiratory Diseases (NCIRD), Centers for Disease Control and Prevention (CDC). This work will be performed at Centers for Disease Control and Prevention (CDC) Roybal Campus in Atlanta, GA. The CDC is the nation's premier health promotion, prevention, and preparedness agency. The Health Scientist I will report to Goldbelt Professional Services leadership to ensure the execution of timely, high-quality deliverables for the client. Health Scientist shall serve as a representative for a comprehensive public health program providing substantive data management leadership, data analysis consultation, database design guidance, and assistance and be responsible for implementation and support of surveillance and other public health program activities in Federal, local, and state settings. Responsibilities Essential Job Functions: - Lead and/or participate in operational or planning meetings to promote data management activities (e.g., data entry, data validation) and gain support and cooperation; assists with developing strategies for program promotion, education, communication, and outreach in collaboration with others. - Plan and coordinate program activities (e.g., manage surveillance data by using SAS), including program implementation (e.g., develop and apply code to test logical and physical database designs and database conversions), service delivery (e.g., create tables, queries, forms and reports in HL7 tables/views), assessment (e.g., reports for use in evaluating program operations), surveillance (e.g., create and modify SAS programs), data quality assurance, partnerships and collaborations, outreach, orientation, training, evaluation and reporting to ensure surveillance and epidemiologic program and project success. - Manage, analyze, and evaluate public health data and surveillance databases. Collect and analyze data from existing or proposed systems, strategies, services, or other data sources to address complex program needs; prepare reports for use in evaluating system operations and other work incidental to the implementation, development and evaluation of the surveillance system. - Monitor and conduct assessments and compliance reviews for program compliance requirements; negotiate and implement corrective actions as needed. Prepare reports of findings, evaluations, and recommendations in terms of strategies, services, and resources. - Develop, implement, and monitor performance evaluation and tracking systems (e.g., maintaining data-correction logbooks and/or files); evaluate and analyze data collection, utilization methods, and quality control. - Perform data analyses as part of a public health program utilizing statistical techniques commonly used in epidemiologic evaluations to interpret and analyze data (e.g., convert existing datasets from a diverse array of file and data formats). Ensure the statistical validity, epidemiologic applicability, and evaluation of program activities (e.g., resolving any inconsistencies in data flow) by participating in data collection, analysis, and report writing. - Consult and collaborate with health-related agencies and other public health partners. - Provides scientific advice and technical assistance (e.g., write business requirements for surveillance data systems) - to health-related agencies and other public health partners for specific surveillance and epidemiologic programs or issues, applying appropriate scientific and technical methods and practices - to develop and implement procedures, methods and strategies for obtaining and using surveillance data, epidemiologic and programmatic data to describe program processes and outcomes (e.g., perform user acceptance testing), morbidity and/or mortality (e.g., SAS data analysis), or the results of a surveillance program or project - to implement, manage, and evaluate surveillance and epidemiologic programs - to jurisdictions to ensure successful implementation and evaluation of funded projects - Participate in the syntheses of surveillance and epidemiologic data for application toward designing effective prevention programs and practice guidelines while ensuring that valid surveillance and program findings are disseminated and applied to surveillance and other public health programs. Qualifications Necessary Skills and Knowledge: - Highly detailed and organized with the ability to manage multiple tasks simultaneously. - Highly proficient in using various statistical software (SAS, R, SPSS, Stata, etc.) - Advanced use of Microsoft Office Tools (Word, Excel, Access, PowerPoint, Publisher) - Ability to work in a fast-paced environment and meet tight deadlines. - Knowledge of the rules, procedures and principles that govern intramural and extramural program development, monitoring, and evaluation. - Ability to use Microsoft Office Applications (Outlook, Word, Excel, PowerPoint, Project, Teams, and SharePoint) efficiently and effectively. - Ability to use and manage CDC Administrative Systems (Human Subjects, OMB and IRB, and E-Clearance) efficiently and effectively. - Able to collaborate with internal CDC partners. Minimum Qualifications: - Bachelor’s or Master’s Degree in Public Health, Epidemiology, Health Sciences Research or a related field. - Minimum 5+ years of relevant experience.    - Clinical or public health background with experience communicating, coordinating, and working with public health programs.   - Experience conducting a systematic assessment of a program or project’s inputs, activities, and outputs to determine its value or worth and to improve the program. - Experience developing an evaluation plan, identifying evaluation questions and indicators, collecting, and analyzing quantitative and qualitative program data, interpreting the data in the context of the program, and reporting findings. - Experience developing a program logic model, identifying appropriate program outcomes, facilitating stakeholder meetings, and providing technical assistance or training on evaluation, methods, concepts, and tools. - Experience performing data analyses as part of a public health program. - Experience providing substantive data management leadership, data analysis consultation, database design guidance. - Ability to obtain and maintain CDC Clearance.  Preferred Qualifications: - Prior experience working with the CDC is highly desired to understand the culture and environment. - Master’s Degree in Public Health or related field. - 3+ years of relevant experience with Master’s Degree. Pay and Benefits The salary range for this position is $90,000 - $92,500 annually. At Goldbelt, we value and reward our team's dedication and hard work. We provide a competitive base salary commensurate with your qualifications and experience. As an employee, you'll enjoy a comprehensive benefits package, including medical, dental, and vision insurance, a 401(k) plan with company matching, tax-deferred savings options, supplementary benefits, paid time off, and professional development opportunities.

• Work with product and customer support teams to turn abstract customer needs into concrete data science problems • Experiment with and evaluate potential solutions to develop high quality prototypes • Work with engineering team to turn prototypes into scalable production-level software • Responsible for projects spanning statistical reasoning, business communications, and software development • Design and execute experiments to evaluate data sampling and data collection strategies

• Use data analysis, visualization, and modeling tools (e.g., Looker, Jupyter Notebooks, Python, Pandas) to drive data-driven business strategies, with a focus on cost prediction for a two-sided marketplace. • Design and execute data science projects, including hypothesis development, statistical analysis, and experimentation (e.g., A/B testing) to answer key business questions and validate assumptions. • Collaborate with cross-functional teams to translate business needs into data science solutions and ensure alignment with Xometry’s objectives. • Analyze existing algorithms for accuracy and performance, provide recommendations for optimization, and update production code as necessary. • Query and extract data from databases (e.g., Snowflake, MongoDB) to support analysis and model development. • Implement robust data science methodologies, emphasizing best practices in code reproducibility, version control, and model deployment. • Continuously iterate and improve solutions within a fast-paced, agile environment, addressing challenges with innovative, data-driven approaches. • Foster a culture of collaboration, teamwork, and continuous learning, encouraging knowledge sharing and skill development within the team.

• Develop, fine-tune, and evaluate Visual Language Models (VLMs) to enhance document understanding, focusing on multimodal data such as text, images, and technical drawings. • Design and implement data preparation, cleaning, and augmentation processes tailored to multimodal model training, ensuring high-quality data pipelines for VLMs. • Leverage transfer learning and pre-trained models to accelerate model development and optimize performance on Xometry’s specific data. • Use cloud resources (e.g., Amazon Web Services) to scale training and fine-tuning processes for VLMs efficiently. • Collaborate with data engineering and machine learning operations (MLOps) teams to deploy VLMs into production and monitor their performance. • Interpret model outputs and improve model accuracy and robustness by applying data analysis and visualization tools (such as Python, Jupyter Notebooks, and SQL). • Experiment with and implement state-of-the-art model architectures, continuously optimizing VLM performance in a fast-paced, iterative environment. • Work within a team-oriented setting, participating in peer reviews, sharing insights, and contributing to an environment of continuous learning and improvement.