Assistant Director of Data Science, Evaluation
- Compensation
- Not disclosed
- Location
- New York, New York, United States
- Work setup
- Hybrid
- Seniority
- Not specified
- Employment
- Full time
- Experience
- 1+ years
- Category
- Data science
- Posted
Skills
Must have
- 3+ years of experience in data science, advanced analytics, or applied statistics, including at least 1-2 years in a leadership, supervisory, or senior individual contributor role.
- Expertise in Python, R, or SQL, with strong experience in machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch).
- Proven ability to design, test, and deploy production-level machine learning models and analytical tools.
- Experience with cloud platforms (AWS, Azure, or Snowflake) and modern data infrastructure (data lakes, data warehouses).
- Experience with the Salesforce platform, including Salesforce Analytics Cloud, Einstein Analytics, or custom data integrations and reporting solutions.
- Strong understanding of data governance, privacy, and ethics in working with sensitive data.
- Ability to translate complex data insights into actionable recommendations for non-technical stakeholders.
- Excellent communication, presentation, and stakeholder management skills.
- Passion for social impact, education, and HCZ’s mission; experience working with youth- or community-focused organizations is a plus.
Full description
Harlem Children’s Zone (HCZ) — a world-renowned education and poverty-fighting organization based in New York — seeks an enthusiastic, dedicated, and mission-aligned Assistant Director of Program Evaluation with our Research & Evaluation Department.
The Assistant Director, Data Science will join our Research & Evaluation team that supports the implementation and maintenance of evaluation systems that promote efficient program information collection and data dissemination within the organization and with our external partners. Working closely with the Director and the Managing Director of Research and Evaluation, the Assistant Director of Data Science is a key member of the department’s management team. Critically, the AD will help lead HCZ’s data science function, driving the development and implementation of advanced analytics, predictive modeling, and data infrastructure to inform decision-making and maximize organizational impact.
For more information, check out Want to Work at Harlem Children’s Zone? Here’s 7 Things You Need to Know.
Requirements
- 3+ years of experience in data science, advanced analytics, or applied statistics, including at least 1-2 years in a leadership, supervisory, or senior individual contributor role.
- Expertise in Python, R, or SQL, with strong experience in machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch).
- Proven ability to design, test, and deploy production-level machine learning models and analytical tools.
- Experience with cloud platforms (AWS, Azure, or Snowflake) and modern data infrastructure (data lakes, data warehouses).
Who you are
- Experience with the Salesforce platform, including Salesforce Analytics Cloud, Einstein Analytics, or custom data integrations and reporting solutions.
- Strong understanding of data governance, privacy, and ethics in working with sensitive data.
- Ability to translate complex data insights into actionable recommendations for non-technical stakeholders.
- Excellent communication, presentation, and stakeholder management skills.
- Passion for social impact, education, and HCZ’s mission; experience working with youth- or community-focused organizations is a plus.
What you’ll do
Leadership & Team Development
- Mentor and provide technical guidance to data science analysts, associates, and administrators contributing to a culture of collaboration, technical excellence, and continuous learning.
- Participate in recruitment processes and support professional development initiatives for team members.
Advanced Analytics & Modeling
- Design and implement machine learning models, predictive analytics, and statistical analyses under the direction of the Director of Data Science.