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About This Role
Department: Technology
Reports to: VP, Data
Travel: \<10%
Salary Range: $99,800 \- $132,300
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:
The Senior Data Scientist is a hands\-on analytical role responsible for building, deploying, and maintaining models and reports that drive evidence\-based decision\-making across Vibrant’s programs and operations. This role supports the full data science lifecycle—from exploratory analysis and model development through deployment, monitoring, and stakeholder communication. The ideal candidate is technically strong, communicates clearly with non\-technical audiences, and is motivated by the opportunity to apply data science in service of mental health and crisis care.
Duties/Responsibilities:
- Design, develop, validate, and deploy predictive models and analytical reports that address core business and programmatic objectives.
- Ensure models and reports are explainable, well\-documented, and accompanied by clear articulation of assumptions, opportunities, and limitations.
- Monitor deployed models for data drift, performance degradation, and quality issues; lead remediation efforts as needed.
- Translate complex analytical findings into accessible insights for program staff, leadership, and external partners.
- Champion data literacy across the organization—partnering with business users to build understanding of how models and reports inform Vibrant’s work.
- Develop and deliver training materials and workshops on data literacy, analytical thinking, and model interpretation.
- Collaborate with data engineers and analytics teams to ensure data pipelines and infrastructure meet modeling and reporting needs.
- Apply statistical and machine learning methods rigorously—selecting appropriate techniques, validating assumptions, and assessing uncertainty.
- Contribute to Vibrant’s data science infrastructure, including model registries, version control, and deployment pipelines on AWS.
- Support ad hoc analytical requests from program and operational teams.
- Additional duties as assigned.
Required Skills/Abilities:
- Strong proficiency in Python and/or R for data analysis, modeling, and reporting; familiarity with relevant libraries (scikit\-learn, pandas, tidyverse, etc.)
- Experience with model development, validation, deployment, and ongoing quality control in a production environment.
- Hands\-on experience with AWS data science services, including SageMaker for model training and deployment.
- Advanced statistical knowledge—including regression, classification, clustering, causal inference, and experimental design.
- Experience working with large, complex datasets in cloud\-based data warehouse environments (Redshift, Snowflake, or similar).
- Excellent written and verbal communication skills—able to present findings clearly to technical and non\-technical audiences alike.
- Strong analytical curiosity, attention to detail, and ability to work independently on ambiguous problems.
- High level of influencing ability.
Required Qualifications:
- Bachelor’s or Master’s degree in a quantitative discipline (statistics, computer science, epidemiology, public health, applied mathematics, or related field), or equivalent applied experience.
- 4\+ years of applied data science experience, including AI/ML model development and code\-based analysis and reporting.
- Experience in public health, behavioral health, social services, or a mission\-driven organization a strong plus.
- Prior experience as a team lead or similar helpful.
- Familiarity with equity\-centered data practices and considerations for algorithmic fairness a plus.
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.
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.
Salary Context
This $99K-$132K range is in the lower quartile for Data Scientist roles in our dataset (median: $155K across 226 roles with salary data).
View full Data Scientist salary data →Role Details
About This Role
Data Scientists extract insights and build predictive models from data. In the AI era, many roles now include LLM-powered analytics, automated reporting, and integration with generative AI tools. The role has evolved from 'the person who runs SQL queries' to 'the person who builds AI-powered data products.'
Modern data science roles fall into two camps: analytics-focused (insights, dashboards, experimentation) and ML-focused (building predictive models, recommendation systems, NLP features). The best data scientists can operate in both modes. The AI shift means that even analytics-focused roles now involve building automated insight pipelines using LLMs, going well beyond one-off reports.
Across the 3,708 AI roles we're tracking, Data Scientist positions make up 8% of the market. At Vibrant Emotional Health, this role fits into their broader AI and engineering organization.
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
What the Work Looks Like
A typical week includes: analyzing experiment results for a product feature launch, building a predictive model for customer churn, creating an automated reporting pipeline using LLM-powered summarization, presenting insights to stakeholders, and cleaning data (always cleaning data). The ratio of analysis to engineering varies by company, but expect both.
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
Skills Required
Python, SQL, and statistical modeling are the foundation. Increasingly, roles want experience with LLMs for data analysis, automated insight generation, and building AI-powered data products. Familiarity with cloud data platforms (Snowflake, BigQuery, Databricks) and ML frameworks (scikit-learn, PyTorch) covers most job requirements.
Experimentation design and causal inference are underrated skills that separate strong candidates. Companies care about whether their product changes cause improvements, and can distinguish causation from correlation. A/B testing methodology, Bayesian statistics, and the ability to communicate uncertainty to non-technical stakeholders are high-value skills.
Good postings specify the data stack, the types of problems you'll work on, and the team structure. Look for companies that differentiate between analytics and ML data science. Vague 'data scientist' postings that list every skill under the sun usually mean the company doesn't know what they need.
Compensation Benchmarks
Data Scientist roles pay a median of $192,890 based on 463 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $230,000. This role's midpoint ($116K) sits 40% below the category median. Disclosed range: $99K to $132K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
Vibrant Emotional Health AI Hiring
Vibrant Emotional Health has 1 open AI role right now. They're hiring across Data Scientist. Based in Remote, US. Compensation range: $132K - $132K.
Remote Work Context
Remote AI roles pay a median of $185,334 across 717 positions. About 14% of all AI roles offer remote work.
Career Path
Common paths into Data Scientist roles include Data Analyst, Statistician, Quantitative Researcher.
From here, career progression typically leads toward Senior Data Scientist, ML Engineer, AI Product Manager.
Start with statistics and SQL. Build a real analysis project on public data that demonstrates insight generation alongside model building. The market values data scientists who can communicate findings clearly to business stakeholders. If you want to move toward ML engineering, invest in software engineering fundamentals and production deployment skills.
What to Expect in Interviews
Interviews combine statistics, coding, and business acumen. SQL is almost always tested, often with complex joins and window functions. Expect a case study round where you're given a business problem and asked to design an analysis plan. Coding rounds focus on pandas, statistical modeling, and visualization. The strongest differentiator is how well you communicate insights to non-technical stakeholders during presentation rounds.
When evaluating opportunities: Good postings specify the data stack, the types of problems you'll work on, and the team structure. Look for companies that differentiate between analytics and ML data science. Vague 'data scientist' postings that list every skill under the sun usually mean the company doesn't know what they need.
AI Hiring Overview
The AI job market has 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 roles).
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
The AI Job Market Today
The AI job market spans 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). 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 (102) are outnumbered by mid-level (1,705) and senior (1,469) 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 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 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 $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. 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 $300,000 median, while Prompt Engineer roles sit at $140,000. 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 (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 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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