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About This Role
Job Title: Research Scientist
Department: Research and Evaluation
Reports to: Lead Research Scientist
Location: Remote
Schedule: Full-time, 9am - 5pm EST Monday - Friday
Salary Grade: $69,000K - $105,000K
Formerly the Mental Health Association of New York City (MHA-NYC), Vibrant Emotional Health’s groundbreaking solutions have delivered high quality services and support, when, where and how people need it for over 50 years. Through our state-of-the-art technology-enabled services, community wellness programs, and advocacy and education work, we are building a society in which emotional wellness can be a reality for everyone.
Position Overview
Under the supervision of the Lead Research Scientist, the Research Scientist supports applied research, evaluation, and evidence synthesis for the 988 Suicide & Crisis Lifeline and other Vibrant research and evaluation activities as applicable. This role designs and conducts independent and collaborative studies, develops and refines data collection tools and methods, and conducts quantitative and qualitative analyses to assess practices, outcomes, and the quality of evidence in crisis service settings. The Research Scientist supports 988 departments in evaluation design and implementation, contributes to literature reviews, and prepares analytic summaries, reports, manuscripts, and other research products. Specific assignments align with the scientist’s area of expertise and organizational priorities to support the continuous improvement of the 988 Lifeline.
Duties/Responsibilities
- Design and conduct independent and collaborative research and evaluation studies that support 988 Lifeline priorities, in coordination with the Lead Research Scientist.
- Conduct quantitative and qualitative analyses using 988 Lifeline data, survey data, pilot data, and other relevant sources.
- Analyze crisis service data to assess practices, outcomes, and opportunities for service improvement.
- Design and support research, pilot studies, and evaluation activities using methods appropriate for crisis service settings.
- Develop, refine, and evaluate surveys, measurement instruments, and other data collection tools to support reliable and meaningful findings.
- Apply appropriate research frameworks and methods to assess the effectiveness, feasibility, and quality of practices, interventions, and measures.
- Support 988 departments in evaluation design, data collection, analysis, and interpretation of findings, with guidance from the Lead Research Scientist as appropriate.
- Maintain and update the biannual literature review, including evidence searches, study summaries, citation tracking, and synthesis of findings.
- Prepare analytic summaries, reports, manuscripts, conference abstracts, presentations, briefs, and other dissemination materials.
- Collaborate with Research and Evaluation colleagues, Lifeline departments, Data Analytics, Data Governance, and other internal partners to support coordinated research and evaluation work.
- Interpret findings considering operational context, research design, data quality, methodological limitations, and implications for practice.
- Maintain transparent documentation of methods, analytic decisions, limitations, and findings.
Required Skills/Abilities
- Strong understanding of applied research, evaluation design, quantitative and qualitative methods, and evidence synthesis.
- Familiarity with research frameworks, study design, measurement approaches, and the application of findings to practice.
- Ability to design studies, data collection tools, and analytic approaches that are feasible in crisis service or public health settings.
- Proficiency in statistical software such as RStudio or comparable tools for quantitative analysis and data visualization.
- Ability to conduct or support qualitative data collection, coding, thematic analysis, and mixed-methods interpretation.
- Ability to select and apply appropriate statistical methods or modeling techniques to complex datasets, including those with missing data.
- Ability to assess data quality, measurement reliability and validity, and methodological limitations as relevant to assigned projects.
- Ability to critically evaluate assumptions, assess alternative explanations, and draw conclusions supported by the evidence.
- Ability to analyze service and research data to identify patterns, assess outcomes, and inform improvement opportunities.
- Ability to translate findings into clear implications for program improvement and decision-making.
- Strong writing skills for preparing analytic summaries, literature reviews, reports, manuscripts, abstracts, and presentations.
- Ability to communicate complex research findings accurately to technical and nontechnical audiences.
- Strong organizational and time-management skills to independently manage multiple projects, timelines, datasets, and stakeholder requests.
- Ability to collaborate across departments and work effectively in a fully remote environment using asynchronous communication tools.
- Familiarity with research ethics, transparent documentation, and reproducible research practices.
- Sound judgment and discretion in handling sensitive research, evaluation, and program data.
- Proficiency with relevant statistical, qualitative, productivity, project management, and collaboration tools.
Decision Making
- Identifies methodological, analytic, implementation, data quality, or interpretation issues that may affect assigned research and evaluation activities.
- Recommends study designs, analytic approaches, data collection strategies, and evaluation methods for assigned projects.
- Determines when data limitations, implementation context, or operational constraints require revised methods, additional caveats, or escalation.
- Analyzes quantitative and qualitative data and recommends interpretations based on evidence, context, and methodological limitations.
- Recommends refinements to pilot designs, implementation measures, data collection tools, or evaluation plans based on emerging findings.
- Escalates complex, high-risk, unclear, or precedent-setting methodological or implementation issues to the Lead Research Scientist.
- Implements approved analytic plans, documentation practices, literature review procedures, and evaluation workflows for assigned work.
Scope of Responsibility/Accountability
- Responsible for conducting assigned research, evaluation, analysis, pilot, and evidence synthesis activities.
- Accountable for the quality, accuracy, documentation, and appropriate interpretation of assigned analyses and research products.
- Supports implementation science-informed evaluation of emerging or refined practices across Lifeline centers.
- Supports 988 departments in developing and implementing evaluation approaches that align with operational needs and research standards.
- Responsible for maintaining assigned portions of the bi-annual literature review and related evidence synthesis materials.
- Contributes to reports, manuscripts, abstracts, presentations, briefs, and other dissemination products.
- Performance is reviewed by the Lead Research Scientist and other leaders as applicable.
Managing/Directing Work
- Manages assigned research, evaluation, analysis, literature review, and pilot study tasks with guidance from the Lead Research Scientist.
- Organizes project timelines, analysis plans, documentation, literature review tasks, and dissemination deliverables.
- Coordinates with internal partners to clarify evaluation questions, data needs, operational context, and implementation considerations.
- Participates in planning, conducting, and interpreting pilot studies and applied evaluation projects.
- Communicates status updates, analytic findings, limitations, risks, and potential roadblocks to the Lead Research Scientist.
- Contributes to improvements in analytic documentation, evaluation workflows, literature review processes, and research-to-practice translation.
- Required Qualifications:
- Ph.D. or equivalent doctoral-level research qualifications in Psychology, Sociology, Public Health, Health Services Research, or a related field required. Equivalent qualifications may include ABD status (All but Dissertation) or, in exceptional cases, a Master’s degree with a substantial record of independent research achievement comparable to doctoral-level preparation.
- 3+ years of relevant experience designing, conducting, analyzing, interpreting, or disseminating research or evaluation studies, with a preference for candidates with 10+ years of experience.
Similarly, minimum of three to five years of relevant experience with:
- Conducting quantitative and/or qualitative analyses and documenting
methods, findings, and limitations.
- Preparing literature reviews, evidence summaries, analytic summaries,
reports, manuscripts, abstracts, or presentations.
- Working with sensitive behavioral health, crisis services, suicide prevention,
overdose prevention, public health, or human services data preferred where
applicable to the role.
- Repeated experience designing or supporting implementation studies, pilot
studies, applied evaluation studies, public health research, behavioral health
research, or crisis services research.
- At least five years of experience applying implementation science
frameworks, translating research into practice, or evaluating emerging
practices in complex, real-world settings is preferred.
Physical Requirements:
- Must be able to remain in a stationary position 50% of the time.
- Will constantly operate a computer and other office productivity machinery, such as a calculator, copy machine, and computer printer.
- Will frequently communicate over video calls with internal and external stakeholders to provide status updates, identify potential roadblocks, and support timely resolution.
We determine base pay through a comprehensive review of skills, experience, education, certifications, geographic location, and other relevant factors. The range listed reflects the compensation parameters for the role and does not represent the full compensation package. A complete overview of compensation and benefits will be provided by the Talent Acquisition team during the hiring process.
Full time employees will be eligible for excellent comprehensive benefits, including medical, dental, vision, supplemental income insurance, employer paid disability insurance, employer paid life insurance, pre-tax FSA for medical and dependent care, and 401K available.
Studies have shown that women and people of color are less likely to apply for jobs unless they believe they are able to perform every task in the job description. We are most interested in finding the best candidate for the job, and that candidate may be one who comes from a less traditional background. Vibrant will consider any equivalent combination of knowledge, skills, education and experience to meet minimum qualifications. If you are interested in applying, we encourage you to think broadly about your background and skill set for the role.
Vibrant Emotional Health is an equal opportunity employer. Applicants are considered for positions without regard to veteran status, uniformed service member status, race, creed, color, religion, gender, gender identity, sex, sexual orientation, citizenship status, national origin, marital status, age, physical or mental disability, genetic information, caregiver status or any other category protected by applicable federal, state or local laws.
Please be aware that fictitious job openings, consulting engagements, solicitations, or employment offers may be circulated on the Internet in an attempt to obtain privileged information, or to induce you to pay a fee for services related to recruitment or training. Vibrant does NOT charge any application, processing, or training fee at any stage of the recruitment or hiring process. All genuine job openings will be posted on our careers page and all communications from the Vibrant recruiting team and/or hiring managers will be from an @vibrant.org email address.
Role Details
About This Role
Research Scientists push the boundaries of what AI can do. They design experiments, develop novel architectures, publish papers, and translate research breakthroughs into production capabilities. This is where the fundamental advances happen, from attention mechanisms to diffusion models to reasoning chains.
The work is intellectually demanding and often ambiguous. You might spend months on an approach that doesn't pan out. The best research scientists combine deep mathematical intuition with engineering pragmatism. They know when to go deep on theory and when to run experiments. They read papers voraciously and can spot incremental contributions from genuine breakthroughs.
Across the 8,943 AI roles we're tracking, Research Scientist positions make up 2% of the market. At Vibrant Emotional Health, this role fits into their broader AI and engineering organization.
Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.
What the Work Looks Like
A typical week includes: reading and discussing recent papers with your team, designing and running experiments on multi-GPU clusters, analyzing results and iterating on hypotheses, writing up findings for internal review or publication, and collaborating with engineering teams to productionize promising results. The ratio of thinking to coding is higher than in engineering roles.
Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.
Skills Required
PhD strongly preferred for most roles. Deep expertise in a specific area (NLP, computer vision, reinforcement learning, multimodal) is expected. PyTorch is the standard. Publication track record matters. Strong mathematical foundations in linear algebra, probability, optimization, and information theory are assumed.
Beyond the fundamentals, companies value experience with large-scale distributed training, novel architecture design, and the ability to bridge theory and practice. Understanding of current frontier topics (reasoning, multimodal, long-context, alignment) is essential. Code quality matters more than many researchers expect. Labs want researchers who can implement their ideas cleanly.
Strong research postings specify the research area, mention the team you'd join, and describe the problems they're working on. They often list recent publications from the team. Vague 'AI research' postings without specifics usually mean the company wants to sound impressive but doesn't have a real research agenda.
Compensation Benchmarks
Research Scientist roles pay a median of $222,200 based on 708 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200.
Across all AI roles, the market median is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,250; VP: $235,000.
Vibrant Emotional Health AI Hiring
Vibrant Emotional Health has 1 open AI role right now. They're hiring across Research Scientist. Based in Remote, US.
Remote Work Context
Remote AI roles pay a median of $185,906 across 2,124 positions. About 6% of all AI roles offer remote work.
Career Path
Common paths into Research Scientist roles include PhD Student, Research Engineer, Postdoc.
From here, career progression typically leads toward Research Lead, Distinguished Scientist, VP of Research.
The PhD is the entry point for most paths. Choose your advisor and research area carefully since they'll define your first industry position. Publish consistently, contribute to open-source projects in your area, and build relationships at conferences. Industry research offers better compensation and compute resources than academia, but the pressure to show product impact is real.
What to Expect in Interviews
Research interviews are multi-stage: a research talk (present your best paper), technical deep-dives on your methodology, and often a 'research proposal' exercise where you design an experiment to test a hypothesis. Coding rounds test implementation ability alongside theoretical knowledge. Be prepared to implement a paper from scratch and discuss the design choices the authors made. Strong candidates can critique papers constructively and identify gaps in experimental methodology.
When evaluating opportunities: Strong research postings specify the research area, mention the team you'd join, and describe the problems they're working on. They often list recent publications from the team. Vague 'AI research' postings without specifics usually mean the company wants to sound impressive but doesn't have a real research agenda.
AI Hiring Overview
The AI job market has 8,943 open positions tracked in our dataset. By seniority: 175 entry-level, 4,132 mid-level, 3,268 senior, and 1,368 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (521 positions). The remaining 8,351 roles require on-site or hybrid attendance.
The market median for AI roles is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 roles).
Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.
The AI Job Market Today
The AI job market spans 8,943 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,739), AI Product Manager (403), AI Software Engineer (402). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (175) are outnumbered by mid-level (4,132) and senior (3,268) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,368 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (521 positions), with 8,351 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $213,380. Top-quartile roles start at $264,148, and the 90th percentile reaches $319,310. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $253,100 median, while Prompt Engineer roles sit at $141,440. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,422 postings), Aws (808 postings), Azure (638 postings), Rag (555 postings), Gcp (457 postings), Pytorch (433 postings), Claude (341 postings), Kubernetes (337 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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