Interested in this Research Scientist role at Abbott?
Apply Now →About This Role
Abbott is a global healthcare leader that helps people live more fully at all stages of life. Our portfolio of life\-changing technologies spans the spectrum of healthcare, with leading businesses and products in diagnostics, medical devices, nutritionals and branded generic medicines. Our 115,000 colleagues serve people in more than 160 countries.
Working at Abbott
At Abbott, you can do work that matters, grow, and learn, care for yourself and your family, be your true self, and live a full life. You’ll also have access to:
- Career development with an international company where you can grow the career you dream of.
- Employees can qualify for free medical coverage in our Health Investment Plan (HIP) PPO medical plan in the next calendar year.
- An excellent retirement savings plan with a high employer contribution.
- Tuition reimbursement, the Freedom 2 Save student debt program, and FreeU education benefit \- an affordable and convenient path to getting a bachelor’s degree.
- A company recognized as a great place to work in dozens of countries worldwide and named one of the most admired companies in the world by Fortune.
- A company that is recognized as one of the best big companies to work for as well as the best place to work for diversity, working mothers, female executives, and scientists.
The Opportunity
This position works out of our La Jolla location in the Cancer Diagnostics Division.
As the Sr. Research Scientist, you’ll have the chance to lead verification and validation studies for innovative NGS\-based multi\-cancer early detection solutions that improve clinical test access, quality, and performance for patients.
Essential Duties
include, but are not limited to the following:
- Drive verification and validation studies to support molecular test product launch in CAP/CLIA clinical laboratory and regulatory submission, including but not limited to: PMA (Pre\-market approval) and IDE (Investigational Device Exemption)
- Lead cross\-functional study design discussion, working closely with multiple departments such as biostatistics, bioinformatics, regulatory, medical director, quality and clinical lab operations
- Serve as technical lead conducting and analyzing NGS experiments across multiple product and technology areas
- Design and optimize NGS\-based solutions that integrate clinical product requirements with analytical and operational performance
- Mentor and provide technical guidance to junior scientists and research associates
- Present experimental results and defend scientific findings at data, group, and project team meetings
- Conduct bench level experiments within several product or technology areas and identify problems and discrepancies.
- Independently develop, plan, and analyze results of bench level experiments within several product or technology areas; effectively present and clearly communicate findings at data meetings, group meetings and project team meetings.
- Analyze research/experimental data, interpret the results, and provide insights into the next steps and the direction of the project.
- Independently develop methods and procedures for new assignments/study/experiments.
- Operate scientific instrumentation related to performance of duties and notify appropriate personnel of any problems.
- Effectively determine, utilize, and apply methods or technologies and provide ideas for new techniques, when appropriate.
- Maintain knowledge of technological industry developments that could assist in completion of an assignment or aid in the development of new processes or procedures.
- Prepare and provide information and data for scientific abstracts/conferences/project meetings/publication.
- Contribute to the intellectual property portfolio by implementing innovative and creative ideas to solve problems or improve on current methods.
- Generate, document, and communicate development plans for critical aspects of a project.
- Develop research plans and experimental outlines to write experimental protocols and perform laboratory experiments.
- Prepare detailed technical procedures, protocols, and reports.
- Evaluate impact of nonconforming data to product or process.
- Identify and address trends in study data.
- Prepare and approve written reports.
- Lead identification of areas for process improvements.
- Maintain lab notebook in a clear, complete, and consistent manner, following all legal, ISO, and QSR requirements.
- Prepare reports and documentation providing highly technical analysis or summarization of experimental results, outcomes, next steps, and the future direction of the project to functional leader, technical teams/groups, or project teams.
- Work on problems which are extremely complex in scope in which analysis of data requires an evaluation of intangible variables.
- Exercise independent judgment in developing methods, techniques, and evaluation criteria for obtaining solutions.
- Work on individual assignments and with project team members, as appropriate, to meet department and project objectives.
- Work within project timeframes with successful outcomes on multiple projects and key responsibilities.
- Act as technical leader for one or more projects that are complex in scope.
- Act as subject matter expert in core team and/or cross\-functional meetings.
- Exercise discretion and independent judgement within broadly defined practices and policies in selecting methods, techniques, and evaluation criteria for obtaining and interpreting results, analyzing data, and presenting findings in a professional and knowledgeable manner.
- Promote an open, collaborative environment built on trust to foster positive teamwork.
- Plan and recommend activities that account for prioritization of organizational and department goals.
- Train, guide, and mentor research associates and junior level Scientists.
- Organize, present, and convey complex problems or issues.
- Ability to communicate clearly and frequently with all levels of the organization; including team members, project team members (core and extended), functional managers, clinical lab, and other stakeholders.
- Create high quality presentations that effectively communicate and tie into a cohesive story the project status and/or experimental results.
- Apply strength in performing complex analyses and the ability to present data and recommendations to a variety of audiences throughout an organization.
- Apply qualitative and analytical skills with strong attention to detail.
- Ability to effectively work on several varied projects at one time, with frequent changing priorities.
- Excellent analytical, problem solving and decision\-making skills.
- Apply technical expertise, scientific creativity and rigor, collaboration with others and independent thought; ability to provide insights and defend scientific ideas.
- Apply experimental knowledge and outcomes to new and valuable problems; ability to make predictions based on a deep understanding of the fundamental nature of the inputs into a decision or action.
- Uphold company mission and values through accountability, innovation, integrity, quality, and teamwork.
- Support and comply with the company’s Quality Management System policies and procedures.
- Regular and reliable attendance.
- Ability to lift up to 20 pounds for approximately 5% of a typical working day.
- Ability to work on a mobile device, tablet, or in front of a computer screen and/or perform typing for approximately 50% of a typical working day.
- Ability to grasp with both hands; pinch with thumb and forefinger; turn with hand/arm; reach above shoulder height.
- Ability to comply with any applicable personal protective equipment requirements.
- Ability to use various types of laboratory equipment including microscopes, microtomes, blades, strainers, and pipettes for extended periods of time.
- May perform repetitious actions using lab tools.
- Ability to use near vision to view samples at close range.
- May be exposed to hazardous materials, tissue specimens and instruments with moving parts, lasers, heating and freezing elements, and high\-speed centrifugation.
Minimum Qualifications
- PhD in life sciences, medical technology, clinical laboratory science, chemical/physical/biological science, or related field; or Master’s degree in life sciences, medical technology, clinical laboratory science, chemical/physical/biological science, or related field and 4 years of related experience in lieu of PhD; or Bachelor’s degree in life sciences, medical technology, clinical laboratory science, chemical/physical/biological science, or related field and 6 years of related experience in lieu of PhD.
- 5\+ years of industry or academia experience in biology and/or chemistry.
- 3\+ years of experience in medical device/IVD, biotech, life science, or pharmaceutical industry.
- Demonstrated ability to apply molecular biology and/or biochemical techniques.
- Demonstrated understanding of GMP, ISO, and Quality Systems.
- Technical expert in the area of molecular biology and/or biochemistry and/or next\-generation sequencing (NGS) and genomics.
- Good knowledge of product/assay research, design, or development.
- Basic working knowledge of statistical and mathematical methods in biology/genetics, including experience with statistical software, such as JMP.
- Proficient computer skills to include Internet navigation, Email usage, and word processing.
- Proficient in Microsoft Office to include Excel and Word and PowerPoint.
- Demonstrated ability to perform the Essential Duties of the position with or without accommodation.
- Authorization to work in the United States without sponsorship.
Preferred Qualifications
- 8\+ years of industry or academic research experience in Life Sciences, Chemistry, or a related field, ideally with hands\-on experience developing, optimizing, and troubleshooting NGS\-based workflows for clinical DNA/RNA samples
- Proficient in NGS data analysis and interpretation, statistical/mathematical methods in biology and genetics (e.g., JMP), and experience with product development in an LDT\- or FDA\-regulated environment.
Apply Now
Learn more about our health and wellness benefits, which provide the security to help you and your family live full lives: https://abbottbenefits.com/
Follow your career aspirations to Abbott for diverse opportunities with a company that can help you build your future and live your best life. Abbott is an Equal Opportunity Employer, committed to employee diversity.
Connect with us at abbott.com, on LinkedIn at https://www.linkedin.com/company/abbott\-/, and on Facebook at https://www.facebook.com/AbbottCareers.
The base pay for this position is $114,000\.00 – $228,000\.00\. In specific locations, the pay range may vary from the range posted.
Salary Context
This $114K-$228K range is below the median for Research Scientist roles in our dataset (median: $195K across 149 roles with salary data).
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 4,317 AI roles we're tracking, Research Scientist positions make up 4% of the market. At Abbott, 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 $222,200 based on 378 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($171K) sits 23% below the category median. Disclosed range: $114K to $228K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Abbott AI Hiring
Abbott has 4 open AI roles right now. They're hiring across Research Scientist, AI Architect, AI/ML Engineer. Positions span La Jolla, CA, US, Waukegan, IL, US, Madison, WI, US. Compensation range: $156K - $298K.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 median).
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 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 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 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). 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 (138) are outnumbered by mid-level (2,071) and senior (1,655) 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 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 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 $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. 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 $287,500 median, while Prompt Engineer roles sit at $145,000. 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 (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 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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