Interested in this Research Scientist role at Clic Nutrition?
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Research Scientist \- Data Expert \+ Health \& Wellness Full Time (Contract with Expansion Opportunity)About Clic \& The Founding Team
Clic is building an advanced individualized supplement platform that will change how people approach daily vitamin and mineral use.
As we head towards the launch of this new product and corresponding technology, we are looking for an individual who has expertise in large\-data sets as well as in nutrition and health. This is an ideal position for a scientist interested in AI\-assisted health and personalization systems. You will be using information gleaned from wearables to assist consumers to individualize their daily supplement strategy.
This start\-up is being generated by a strong team that has a proven track record of taking startups to multi\-billion dollar valuations. We are looking for an individual that will be part of this innovation as we launch into the international health market.
Position Overview
We are looking for a dynamic, creative thinker who will work directly with the founding team on the scientific framework for Clic Nutrition.
The ideal candidate combines rigorous scientific thinking, preferably at a PhD level, with the ability to operate effectively in a fast\-moving startup environment.
Responsibilities
- Research and synthesize peer\-reviewed literature across supplement ingredients, dosing, efficacy, interactions, and safety considerations;
- Help design and validate the scientific logic behind Clic’s recommendation engine \- creating algorithms in collaboration with the data team and feedback loops that personalize each consumer’s daily supplement use;
- Develop frameworks that map biomarker inputs, lab data, wearable outputs, and health goals to personalized supplement recommendations;
- Validate and stress\-test recommendation outputs for scientific accuracy, safety, and clinical relevance;
- Translate complex scientific findings into structured documentation and usable data formats that support product development;
- Collaborate closely with founders, production teams, and operations teams to ensure scientific integrity is embedded throughout the consumer recommendation pipeline;
- Identify contraindications, safety concerns, and population\-specific sensitivities within the recommendation logic
- Support ongoing refinement of ingredient protocols (ie dose, timing etc) and personalization frameworks as the platform evolves
Ideal Experience
- 2\+ years applied experience post\-graduate
- Advanced degree (MSc or PhD preferred) in:
- Epidemiology and Biostatistics in large data set analyses
- Wellness and Individualized Health care \- Nutrition Science
- AI and large\-date driven health decision analyses
- or a closely related scientific field
- reviewing and applying clinical research with the ability to assess real\-world relevance and quality of evidence
- Deep understanding of:
- supplement ingredients
- micronutrients
- mechanisms of action
- dosing frameworks
- Familiarity with biomarker interpretation
- blood panels
- hormone markers
- nutrient deficiency indicators
- wearable health data \& biometrics
- Experience structuring scientific information into protocols, frameworks, decision trees, or clinical\-style recommendation systems
- Ability to communicate complex scientific concepts clearly to non\-technical stakeholders
- Familiarity with FDA, FTC, and DSHEA, and the boundaries between structure/function claims and disease claims
- Comfortable operating independently in high\-growth startup environments
Preferred Skills
- Experience working with personalized health, longevity, or wellness products
- Familiarity with decision\-tree logic or recommendation systems
- Understanding of functional medicine, preventative health, or systems biology
- Experience organizing scientific research into scalable operational frameworks
Engagement Details
- Contract role \- with possibility of full time position
- Immediate start preferred
- Remote\-friendly
- High level of collaboration with founders and product team
- Potential for long\-term/full\-time opportunity as the company scales
What we are looking for
- Scientific rigor
- A background in personalized health and wellness
- Understanding of the area of evidence\-based supplementation
- Building foundational systems from the ground up
This is not a traditional corporate research role \- we’re looking for someone excited to help build the scientific backbone of a next\-generation personalized wellness platform.
To apply, please send:
- Resume / CV
- Brief introduction
- Relevant research or scientific experience
- Availability / timezone
- Compensation expectations
Work Location: Remote
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 3,823 AI roles we're tracking, Research Scientist positions make up 3% of the market. At Clic Nutrition, 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 in Demand for This Role
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 $223,400 based on 280 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $165,000.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
Clic Nutrition AI Hiring
Clic Nutrition 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 $170,000 across 1,926 positions. About 15% 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 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 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 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). 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 (112) are outnumbered by mid-level (1,798) and senior (1,516) 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 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 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 $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. 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 Engineering Manager roles lead at $275,000 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 (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 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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