Research Associate I - Opioid Policy Research Collaborative

Now Hiring: Research Associate I - Opioid Policy Research Collaborative at
Brandeis University |

Do you believe data can save lives? Do you want your work to directly shape public health responses and support people impacted by the overdose crisis? Join a mission-driven research team using real-time drug supply intelligence to create safer, healthier communities.

This project is led by nationally recognized harm-reduction researcher Dr. Traci Green, are seeking a Research Associate I who is passionate about transforming complex data into clear, meaningful stories that drive change. This is a unique opportunity to blend data science, public health, and social justice in one impactful role.

To apply, please submit a cover letter and resume/CV.

The hiring range for this position is $51,300 - $64,100.

What You Will Do

As a Research Associate I, you will be at the heart of our community-based harm reduction efforts. You will:

• Lead the design of data visualizations and interactive dashboards using the StreetCheck platform that illuminate trends in the local drug supply (25%).
• Collaborate with analysts and researchers to translate scientific findings into compelling visuals for reports, manuscripts, presentations, and digital tools (20%).
• Build and maintain visualization systems and data pipelines to ensure clean, connected, and analysis-ready datasets (15%).
• Establish visual standards and oversee quality assurance, ensuring all visuals are accurate, accessible, and equity-centered (15%).
• Innovate new approaches to data storytelling, including interactive features, maps, and dynamic summaries that amplify community and policy impact (10%).
• Produce visuals for research papers and presentations that strengthen the narrative and highlight key findings (5%).
• Work collaboratively with diverse community and institutional partners, communicating data clearly to audiences of all backgrounds (5%).
• Train teammates on tools and methods, offering technical support where needed (5%).

What We Are Looking For

• Master’s degree in a quantitative-focused social science or business field
• Strong data visualization skills (charts, maps, dashboards, web tools)
• Experience with visualization best practices and data pipeline development
• Clear communicator who can translate complex results for technical and non-technical audiences
• Compassion, respect, and commitment to treating people who use drugs and people in recovery with dignity
• Ideally, experience working with harm reduction, vulnerable populations, or community health
• A collaborative spirit and curiosity for innovative data storytelling

Why This Role Matters

The overdose crisis continues to evolve, and communities rely on accurate, accessible, real-time data to stay safe. Your work will directly support harm-reduction practitioners, policymakers, and people who use drugs—helping ensure they have the information they need to make informed decisions.

This position is fully grant-funded and part of a dynamic, supportive research environment dedicated to ethical, community-anchored public health work.

Ready to Make an Impact?

Apply today and help turn data into action, insight into empathy, and evidence into change.
Be part of a team that believes every dataset tells a story—and that story can save lives.

Pay Range Disclosure

The University's pay ranges represent a good faith estimate of what Brandeis reasonably expects to pay for a position at the time of posting. The pay offered to a selected candidate during hiring will be based on factors such as (but not limited to) the scope and responsibilities of the position, the candidate's work experience and education/training, internal peer equity, and applicable legal requirements.

Equal Opportunity Statement

Brandeis University is an equal opportunity employer which does not discriminate against any applicant or employee on the basis of race, color, ancestry, religious creed, gender identity and expression, national or ethnic origin, sex, sexual orientation, pregnancy, age, genetic information, disability, caste, military or veteran status or any other category protected by law (also known as membership in a "protected class").