Senior Manager, Data Science

ASPCA
2d$93,000 - $117,000Remote

About The Position

Every year, millions of animals enter shelters across the United States -- and the data behind their stories has the power to transform how shelters and communities care for them. As Senior Manager of Data Science at Shelter Animals Count (a Program of the ASPCA), you'll be at the center of the nation's most comprehensive effort to collect, analyze, and share animal sheltering data. Your work will directly shape the estimates, models, and insights that guide policy, improve shelter operations, and ultimately improve animal welfare. If you're a data scientist who loves data analysis and machine learning and wants your skills to drive real-world impact for animals and the communities that serve them, this is your role. The Senior Manager, Data Science reports to the Senior Director, Research & Data Science, and will work closely with other members of the Shelter Animals Count (SAC) and broader Strategy team. They will work on data analysis projects and refine and maintain the machine learning models that power SAC's national estimates of shelter animal intakes, outcomes, and population trends. They will also work closely with a diverse group of stakeholders, external partners, interns, contractors, and vendors to execute key programmatic objectives as outlined in SAC’s plan. They will bring a high level of expertise and integrity in data science, analytics, and reporting. Shelter Animals Count (SAC) is a nationally recognized brand dedicated to collecting, analyzing, and sharing data on animal sheltering across the United States and Canada, and will join the ASPCA’s Strategy Team. The Strategy department has five verticals: Strategy and Planning, Research, Impact Measurement and Data Science, Project Management Office, and SAC. The Strategy team uses strategic and data-driven processes to guide organizational direction, drive effective decision-making, and deliver actionable, evidence-based insights to shelters and communities. Strategy serves as a thought partner to ASPCA departments; facilitates collaboration among departments; and connects the dots to maximize efforts to drive our goals forward. Shelter Animals Count, established in 2012, is dedicated to collecting and sharing reliable shelter data to improve welfare and outcomes for animals and communities. By serving as a neutral, industry-wide data collection entity, Shelter Animals Count provides valuable insights into shelter operations, trends in animal welfare, intake and outcomes, and the challenges faced by shelters, rescues, and communities. Shelter Animals Count collaborates with organizations of all sizes to encourage data submission, fostering a comprehensive understanding of the state of animal welfare. This data-driven approach supports evidence-based decision-making, ultimately helping to improve welfare and outcomes for animals, guide policy, and increase transparency within the animal welfare community. You will lead SAC's data science and analytical work -- building and improving estimation and forecasting models, ensuring data quality and methodological rigor, and translating complex datasets into actionable insights for partners, shelters, and the public. You'll also collaborate on data reporting, data visualization/dashboarding and peer-reviewed research, and represent SAC's data expertise both internally and at national conferences. This role involves hands-on work with Shelter Animals Count's database (for example, frequent analysis of datasets including 20M+ animals, many parameters). The ideal candidate should be comfortable working at scale, building and validating statistical and machine learning models, and owning the full analytical pipeline from raw data to published estimates. The Senior Manager, Data Science, reports directly to the Senior Director, Research & Data Science and has 0 direct reports. This remote-based position (which requires travel, as described below) is open to all eligible candidates based within the United States. The schedule for this position is generally Monday-Friday 9am-5pm (flexibility needed, as some early mornings, evenings, and weekends will be required.) Ability and willingness to travel up to 10% annually as needed.

Requirements

  • Demonstrated ability to analyze and draw conclusions from large volumes of data and information with a high level of accuracy and integrity.
  • Extensive knowledge of and experience with data analysis tools (Python, R, SQL, etc.)
  • Extensive knowledge of and experience with data visualization tools (Tableau/Tableau Prep/Power BI, or similar)
  • Demonstrated knowledge and experience applying statistical and machine learning techniques -- including descriptive, inferential, estimation, and forecasting methods -- to generate insights and support data-driven decision-making.
  • Experience with or enthusiasm for using AI-assisted development tools (e.g., Claude Code, GitHub Copilot) to accelerate data science workflows.
  • Self‐motivated individual capable of working independently; managing priorities across multiple, concurrent programs and initiatives; and remaining curious about the data to stretch beyond questions asked.
  • Ability to exemplify ASPCA’s core values and behavioral competencies
  • Advanced degree in Data Analytics, Data Science, or related field preferred or equivalent work experience.
  • 5 years of combined experience in statistical analysis, machine learning, programming for data science, data interpretation, data reporting and research within academic, non-profit, business, and/or related fields required.
  • Experience working with large-scale datasets (millions of records) and deriving meaningful insights from complex, multi-dimensional data required.
  • Experience with data visualization and analytics tools required (Tableau/Tableau Prep/Power BI, SQL, Python, R, or similar) required
  • English (Required)

Nice To Haves

  • Familiarity with animal welfare and animal sheltering data collection and analysis is preferred.

Responsibilities

  • Serve as a subject matter expert on national datasets, providing data and analytical support to advance SAC deliverables and industry collaborations.
  • Advance innovation, creative problem solving, and cross-departmental collaboration to improve outcomes and processes.
  • Apply best practices in data science, including univariate and multivariate statistical techniques and machine learning, to derive insights from large and complex datasets to inform understanding and decision-making.
  • Oversee, enhance, and maintain SAC’s machine learning estimation and forecasting models.
  • Identify, evaluate, and report on new data sources to strengthen and broaden insights into animal welfare, sheltering, and community trends.
  • Demonstrate intellectual curiosity by proactively exploring data for additional insights beyond initial inquiries.
  • Automate data analysis workflows to enhance efficiency and reproducibility.
  • Clearly annotate and document all code to support transparency, collaboration, and long-term maintainability.
  • Collaborate on data analysis for peer-reviewed research projects, contributing to rigorous methodology, interpretation, and publication.
  • Partner with the broader SAC program and ASPCA team to fulfill media and partner data requests, ensuring timely, accurate statistics, clear methodology explanations, and actionable insights.
  • Develop, build, and maintain reports, Tableau dashboards, and processes to monitor data quality, integrity, and overall efficiency.
  • Build strong, supportive working relationships across teams and departments to advance shared goals.
  • Adapt to change with flexibility, curiosity, and a solutions-oriented mindset.
  • Represent SAC data and reporting at conferences throughout the year, providing in-person data analytics expertise.
  • Adhere to and promote data governance policies, business rules, and definitions to ensure consistent program evaluation and measurement.
  • Support across the SAC team in implementing improved data governance processes, including workflow design, business rules, role permissions, quality assurance, approval, and publishing protocols.
  • Streamline and automate manual processes to ensure the most current data is readily available to business users.
  • Occasionally recruit, train and manage Data Science interns on short- and long-term data projects, providing mentorship and guidance while continuously developing collaborative workflows to support ongoing priority initiatives.

Benefits

  • Affordable health coverage, including medical, employer-paid dental, and optional vision coverage.
  • Flexible time off that includes vacation time, sick and bereavement time, paid parental leave, 10 company paid holidays, and paid personal time off that allows you even more flexibility to observe the days that mean the most to you.
  • Competitive financial incentives and retirement savings, including a 401(k) plan with generous employer contributions — we match dollar for dollar up to 4% and provide an additional 4% contribution toward your future each year.
  • Robust professional development opportunities including classes, on-the-job training, coaching and mentorship with industry-leading peers, internal mobility, opportunities to support in the field, and so much more.
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