Senior Data Scientist

The Data Scientist will play a key role in transforming raw data into actionable insights that guide ACF’s mission of supporting children and families. This role encompasses end-to-end data science solutions—from data collection and cleaning, to statistical modeling, to communicating insights and findings with stakeholders. The ideal candidate will have deep technical skills in data analysis, machine learning, and statistical methodologies, complemented by a strong understanding of (or interest in) ACF’s mission areas—including child welfare, child care, child support, Head Start, and other human services programs. Key Responsibilities Data Exploration & Preparation Acquire, clean, and organize large, complex data sets from internal and external sources. Conduct exploratory data analysis (EDA) to uncover trends, patterns, and insights related to ACF’s programs. Model Development & Advanced Analytics Develop, validate, and deploy predictive models using statistical, machine learning, or artificial intelligence methods. Perform hypothesis testing, A/B testing, and time-series analysis to enhance program evaluation and inform policy decisions. Use quantitative and qualitative methods to identify actionable insights that can improve program outcomes. Visualization & Reporting Build interactive dashboards and data visualizations (e.g., Power BI, Tableau, R Shiny) to present findings clearly to non-technical stakeholders. Clearly communicate complex analytical concepts and results through briefs, reports, and presentations that inform decisions at all levels. Collaboration & Stakeholder Engagement Partner with cross-functional teams, including program managers, policy analysts, data engineers, and IT specialists, to integrate analytics into business processes. Collaborate closely with subject matter experts in child welfare, child care, child support, and other programs to understand data context, constraints, and opportunities. Data Governance & Compliance Adhere to and help shape data governance policies ensuring data privacy, security, and quality in accordance with federal standards (FERPA, HIPAA, etc.). Maintain thorough documentation of data sets, methodologies, models, and findings to ensure reproducibility and compliance with audit requirements. Continuous Improvement Stay abreast of industry best practices, emerging tools, and novel analytical approaches. Provide recommendations for technology and process improvements to enhance the organization’s data science capabilities. Required Qualifications Education & Experience Bachelor’s degree in Data Science, Statistics, Computer Science, or a related field; Master’s or Ph.D. preferred. 3+ years of hands-on experience in data science, machine learning, or statistical modeling. Demonstrated success in building and deploying analytical models in a production or policy environment. Technical Skills Proficiency in one or more programming languages (e.g., Python, R, SQL) for data manipulation, analysis, and modeling. Familiarity with data visualization and business intelligence tools (Tableau, Power BI, R Shiny, etc.). Strong grounding in statistical methods, machine learning techniques (e.g., regression, classification, clustering, NLP), and model evaluation. Experience with cloud-based data and analytics platforms (AWS, Azure, GCP) or on-premises big data ecosystems is a plus. Soft Skills Excellent communication skills to present complex findings in a clear, concise manner to diverse audiences. Detail-oriented, with strong problem-solving and analytical thinking abilities. Ability to work collaboratively across interdisciplinary teams, balancing multiple projects and deadlines.