Role Description Goldbelt Professional Services, LLC is seeking a Temporary Junior Data Scientist to work with the Center for Forecasting and Outbreak Analytics, as part of the Office of the Director. This will be a remote position working with the Centers for Disease Control and Prevention (CDC). These Temporary Junior Data Scientist positions will report to Goldbelt Professional Services leadership to ensure the execution of timely, high-quality deliverables for the client. This is a Remote Temporary position that will end on or around August 31st contingent on funding, but may go until October. Responsibilities - Collaborate with CFA data scientists to characterize and summarize variations in various data sources/systems. - Apply data science and machine learning methods (e.g., principal component analysis and clustering) to identify data characteristics. - Conduct exploratory regression analyses to examine how identified data relate to disease outbreaks, with the goal of informing future intervention strategies. Qualifications - Attention to detail is necessary to ensure the client receives up to date and correct information. - Be proactive when approaching problems in daily work. - Attempt to troubleshoot issues and discuss solutions with mentors. - Excellent written and verbal communication in interpersonal exchanges. - Exhibit initiative and ability to work autonomously and in a team environment. - Outstanding judgment and decision making, demonstrating analytical and organizational skills. - Working towards a Bachelor’s degree in Public Health, Statistics, Data science, computer science, information technology, or related field. - Demonstrate excellent written and verbal communication in interpersonal exchanges. - Detailed and organized with the ability to manage multiple tasks simultaneously. - Familiar with a variety of software (SAS, R, SPSS, Stata, Python, C++). - Familiar with the use of Microsoft Office Tools (Word, Excel, Access, PowerPoint, Publisher). Preferred Qualifications - Bachelor's or Master’s degree in public health, statistics, data science, computer science, information technology, or related field. Benefits - The pay range for this position is $35 to $37 hourly. - Competitive base salary commensurate with your qualifications and experience. - Comprehensive benefits package, including medical, dental, and vision insurance. - 401(k) plan with company matching. - Tax-deferred savings options. - Supplementary benefits. - Paid time off. - Professional development opportunities.

• Develop and evolve statistical and causal inference methodologies that strengthen the rigor and reliability of Northbeam’s marketing measurement products • Enhance the accuracy, robustness, and scalability of existing MMM pipelines • Write production-quality Python and SQL, collaborating closely with Engineering to integrate statistical workflows into scalable systems • Rigorously assess model assumptions, identify potential sources of bias, and implement mitigation strategies • Debug data and modeling issues in production and improve the reliability of customer-facing results • Translate complex statistical reasoning into clear, decision-ready insights for internal stakeholders and customers

• Own the analytical strategy for a product area: identifying the highest-leverage questions, defining the measurement framework, and ensuring data-driven decisions • Serve as a strategic partner to product and engineering leadership, translating ambiguous business problems into analytical approaches and clear, actionable recommendations • Define north-star metrics and measurement strategies to set goals, evaluate progress, and make trade-offs • Design and oversee experiments and causal analyses, ensuring methodological rigor and that results drive real product decisions • Develop and maintain a deep understanding of user growth dynamics: how acquisition, activation, and retention interact to drive growth, and use that understanding to diagnose metric movements, explain trends to leadership, and anticipate emerging risks or opportunities • Contribute and own areas of the team’s forecasting and growth modeling efforts, helping translate statistical models into actionable growth strategies • Mentor and elevate other data scientists through code review, methodology guidance, and establishing reusable analytical frameworks • Represent data science in cross-functional forums, making the case for what the data shows even when it challenges prevailing assumptions • Drive alignment across data science, data engineering, and product on shared priorities like data quality, metric definitions, and instrumentation

• Collect, analyze, and interpret large datasets to extract valuable insights • Develop and implement statistical models and algorithms • Perform exploratory data analysis to identify patterns • Build and maintain data pipelines • Develop data visualizations and reports • Collaborate with multidisciplinary teams • Evaluate and select appropriate tools and technologies • Stay up to date with the latest trends