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Director Research & Evaluation Jobs (NOW HIRING)

The Bronx

Director of Research & Evaluation

Houston, TX · On-site

$120 - $130/hr

Position Overview Scion Nonprofit Staffing has been engaged to conduct a search for a Director of Research & Evaluation for a nationally recognized science, education, and cultural institution. This ...

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City of New York

Director of Research

Manhattan, NY

The Director is responsible for leading the Office's research, evaluation, and evidence-building agenda, ensuring that agency strategies, programs, and investments are informed by data, research, and ...

City of New York

Director of Research

Manhattan, NY · On-site

The Director is responsible for leading the Office's research, evaluation, and evidence-building agenda, ensuring that agency strategies, programs, and investments are informed by data, research, and ...

City of New York

Director of Research

Manhattan, NY · On-site

$150K/yr

The Director is responsible for leading the Office's research, evaluation, and evidence-building agenda, ensuring that agency strategies, programs, and investments are informed by data, research, and ...

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How much do director research & evaluation jobs pay per year?

As of Aug 8, 2026, the average yearly pay for director research & evaluation in the United States is $119,966.00, according to ZipRecruiter salary data. Most workers in this role earn between $107,000.00 and $141,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a director research & evaluation?

To thrive as a Director Research & Evaluation, you need a strong background in research methodologies, data analysis, program evaluation, and a relevant advanced degree, such as a master's or PhD. Familiarity with statistical software (e.g., SPSS, R, or SAS), project management tools, and certifications like PMP or evaluation-specific credentials is highly beneficial. Exceptional leadership, strategic thinking, and communication skills enable effective team management and clear reporting of findings to diverse stakeholders. These abilities ensure accurate, actionable insights that drive organizational improvement and evidence-based decision-making.

What is a director research & evaluation?

A Director of Research & Evaluation oversees data collection, analysis, and assessment to measure program effectiveness and inform strategic decisions. They design research methodologies, develop evaluation frameworks, and ensure the accuracy and integrity of findings. This role often involves collaborating with stakeholders, managing research teams, and presenting insights to guide organizational improvements.

What are the typical challenges faced by a director research & evaluation, and how can they be addressed?

Directors of Research & Evaluation often navigate challenges such as managing multiple complex projects simultaneously, aligning research goals with organizational objectives, and ensuring data quality and integrity. They may also face the need to communicate technical findings to non-expert audiences and secure stakeholder buy-in for evaluation recommendations. Success in this role often depends on strong organizational skills, adaptive communication, and a proactive approach to engaging cross-functional teams. Developing standardized protocols and fostering collaborative relationships can greatly help in overcoming these challenges and driving impactful research outcomes.

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Director Research Evaluation jobs near you
Infographic showing various Director Research & Evaluation job openings in the United States as of August 2026, with employment types broken down into 100% Full Time. Highlights an 57% In-person, 14% Hybrid, and 29% Remote job distribution, with an average salary of $119,966 per year, or $57.7 per hour.

Director, Research - Evaluation & Training

Snorkel AI

San Francisco, CA • On-site

Full-time

Re-posted 27 days ago

Job description

ABOUT THE ROLE 

We're looking for a manager to lead a team of researchers to focus on data evaluation, error analysis and data valuation methods to predict model performance. This team is responsible for showcasing the value and quality of Snorkel's data for model training and evaluation, understanding where today's frontier models fall short, and turning that understanding into a point of view on what benchmarks and datasets these models will benefit from. 

You and your team will be responsible for Snorkel's data design flywheel by analyzing model failures, finding capability and skill gaps in current models, suggesting the next benchmarks to invest in and then proving the value of this data for our customers. 

MAIN RESPONSIBILITIES 

  • Own a multi-quarter roadmap centered on novel evaluation, error analysis, and data valuation techniques
  • Synthesize and share trends from model-failure analysis and benchmarking into recommendations on the datasets the community should focus on and the ones Snorkel should invest in - making this team a primary input to the company's data strategy.
  • Focus on data valuation techniques that quantify how Snorkel data meaningfully improves model performance
  • Lead and grow a team of researchers, setting a high bar for quality, rigor and speed of execution
  • Act as the primary bridge between the team's findings and Product, GTM, and our customers

PREFERRED QUALIFICATIONS 

  • 7+ years in applied AI, ML, or research roles, with 4+ years managing technical teams.
  • A leader who has repeatedly turned research and analysis into business outcomes, and who instinctively connects technical findings to market and customer needs.
  • Strong business and market judgment in the AI/ML space - you understand the competitive and frontier-lab landscape and can prioritize accordingly.
  • Technically conversant and credible: enough depth in LLM evaluation, benchmarking, and model behavior analysis to set direction, judge experimental quality, and pressure-test results - without needing to be the deepest technical expert in the room.
  • A nose for trends: able to look across many evaluation results and failure cases and extract the signal that should drive what gets built next.
  • Excellent communication and storytelling skills, with the ability to make technical results legible and persuasive to non-research audiences.
  • Familiarity with data valuation or data attribution research is a strong plus.
  • Bonus: experience working with frontier labs, public benchmarks, or commercial AI data/eval products.

Apply