Interested in this Research Scientist role at Taiho Oncology?
Apply Now →About This Role
Looking for a chance to make a meaningful difference in the oncology space? Taiho Oncology is on a mission: to improve the lives of patients with cancer, their families, and caregivers. Our “People first” approach means we also highly value our employees, who work relentlessly to help execute our mission. Taiho’s success is founded on ensuring we always act with accountability, collaboration, and trust. By following these guiding principles, we earn and maintain the confidence of patients, the global healthcare community, collaborators and partners, and each other. Together, we are working on cutting\-edge science and growing our portfolio and pipeline across a range of tumor types to address the ongoing and evolving needs of patients. Advanced technology, a world\-class clinical development organization, and state\-of\-the\-art facilities: these and other resources empower us to innovate and touch the lives of more and more patients. It’s our work, our passion, and our legacy. We invite you to join us.
Hybrid
Employee Value Proposition:
At Taiho Oncology, we are dedicated to transforming the landscape of cancer treatment and improving patients' lives. As a Director, Clinical Research Scientist, you will play a pivotal role in our mission, leveraging your expertise to drive innovative clinical research and contribute to groundbreaking therapies. We offer a collaborative and inclusive work environment where your ideas and contributions are valued. Join us to advance your career, work with passionate and skilled professionals, and make a meaningful impact on the fight against cancer. At Taiho Oncology, you will find purpose, growth, and the opportunity to be at the forefront of cancer research.
Position Summary:
The Director, Clinical Research Scientist has responsibility assisting in design, execution and reporting of current and future clinical oncology trials ranging from phase 1 \- 3\. Additionally, this role serves in assisting the responsible medical monitor or a Lead medical monitor for various clinical phase 1 \- 3 trials, and assisting the Clinical Research Scientist Manager to contribute to CRS process improvement, as needed.
Performance Objectives:
- Uses medical/scientific expertise to support the creation of relevant clinical documents of high quality such as study concepts, study protocols, amendments, study reports and investigator brochures.
- At the asset level, assists the medical lead in the preparations of the clinical content of regulatory submissions/documents (e. g. NDA, MAA, IND, CTA. sNDA, DSUR, PIP, health authority/ethics committee responses, briefing packages).
- Works with the medical lead to prepare presentations (internal and external), abstracts, manuscripts.
- Inputs into the of ICF/reviews ICF.
- Works with data management on CRF design and completion guide.
- Partners with data management to develop data review plan for review of data and with medical lead for the medical monitoring plan.
- Reviews protocol deviations, patient eligibility, and patient level and cumulative data per the data review plan across a study, raises queries and coordinates with the medical lead.
- Reviews safety data with the medical lead, SAE reports (in collaboration with pharmacovigilance), labs, efficacy data, dosing data, withdrawals/discontinuations.
- Collaborates with the medical lead to provide medical/scientific guidance during the execution of the study.
- Ensures TMF compliance for clinical development/medical study level TMF documents.
- Answers specific site protocol questions as needed, after consultation with the medical lead.
- Develops specific medical/protocol training for Site Initiation Visits and Investigator Meetings, vendor / CRO staff, in collaboration with the medical lead.
- Escalates protocol\-related issues requiring complex medical expertise to the medical lead, and operational issues to the appropriate operations study team member.
- Reviews the SAP and statistical outputs, in collaboration with the statistician, medical writer, and medical lead.
- Reviews the CSR (interim; final; addendum), in collaboration with the medical writer and medical lead and/or any related publications (abstracts; presentations at meetings or publications in scientific journals) in relation with medical writer and medical lead.
- Assist in any other asset activities requiring clinical/ scientific expertise.
Education/Certification Requirements:
- PhD, PharmD or other related Advanced Medical Scientific Degree.
- Experience in oncology is a must.
Knowledge, Skills, and Abilities:
- At least 3 years in drug development industry in oncology and with previous exposure to clinical development, regulatory and statistical activities such as, e.g., (co\-)authoring and reviewing of documents.
- Ability to critically review and interpret Clinical data.
- Working knowledge of the drug development process in the USA and EU is required.
- Ability to learn, integrate complex information, and communicate clinical information in easily understandable fashion to non\-clinical team members.
- Ability to follow independently delegated activity linked to clinical research scientist function, communicate progress and understand timelines.
The pay range for this position at commencement of employment is expected to be between $238,000\- $280,000 annually. This pay range is based on the market range for positions of this type. However, base pay offered may vary depending on multiple individualized factors, including market location, job\-related knowledge, skills, and experience. The total compensation package for this position may also include other elements, including annual bonus/incentive comp plans, potential long term incentive plan, and discretionary awards in addition to a full range of medical, financial, and/or other benefits (including 401(k) eligibility and various paid time off benefits, such as vacation, sick time, and parental leave), dependent on the position offered. Details of participation in these benefit plans will be provided if a candidate/employee receives an offer of employment.
If hired, employee will be in an “at\-will position” and the Company reserves the right to modify base salary (as well as any other discretionary payment or compensation program) at any time, including for reasons related to individual performance, Company or individual department/team performance, and market factors.
\#Location\-Princeton,NJ / \#Location\-Pleasanton, CA \#LI\-Hybrid
Equal Opportunity Employer Information: Taiho Oncology is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, gender, sex, age, religion, creed, national origin, ancestry, citizenship, marital status, sexual orientation, physical or mental disability, medical condition, veteran status, gender identity, genetic information, or any other characteristic protected by federal, state, or local law. Any applicant who, because of a disability, needs an accommodation or assistance in completing an application or at any time during the application process, please email [email protected]. Taiho Oncology also provides reasonable accommodations to employees with disabilities consistent with our obligations under the law. Pursuant to applicable state and municipal Fair Chance Laws and Ordinances, we will consider for employment qualified applicants with arrest and conviction records.
The incumbent in this position may be required to perform other duties, as assigned.
Salary Context
This $238K-$280K range is above the 75th percentile for Research Scientist roles in our dataset (median: $183K across 117 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 4,133 AI roles we're tracking, Research Scientist positions make up 3% of the market. At Taiho Oncology, 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 307 positions with disclosed compensation. Director-level AI roles across all categories have a median of $250,000. This role's midpoint ($259K) sits 16% above the category median. Disclosed range: $238K to $280K.
Across all AI roles, the market median is $200,700. Top-quartile compensation starts at $254,000. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Safety ($274,200) and AI Engineering Manager ($268,700). By seniority level: Entry: $97,760; Mid: $165,778; Senior: $227,400; Director: $250,000; VP: $250,000.
Taiho Oncology AI Hiring
Taiho Oncology has 1 open AI role right now. They're hiring across Research Scientist. Based in Princeton, NJ, US. Compensation range: $280K - $280K.
Location Context
Across all AI roles, 14% (583 positions) offer remote work, while 3,532 require on-site attendance. Top AI hiring metros: New York (2,760 roles, $211,000 median); San Francisco (2,258 roles, $253,000 median); Los Angeles (1,841 roles, $195,000 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 4,133 open positions tracked in our dataset. By seniority: 106 entry-level, 1,901 mid-level, 1,663 senior, and 463 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (583 positions). The remaining 3,532 roles require on-site or hybrid attendance.
The market median for AI roles is $200,700. Top-quartile compensation starts at $254,000. The 90th percentile reaches $307,500. Highest-paying categories: AI Safety ($274,200 median, 57 roles); AI Engineering Manager ($268,700 median, 42 roles); Research Engineer ($260,000 median, 442 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 4,133 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,865), Data Scientist (339), AI Software Engineer (313). 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 (106) are outnumbered by mid-level (1,901) and senior (1,663) 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 463 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (583 positions), with 3,532 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 $200,700. Top-quartile roles start at $254,000, 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 Safety roles lead at $274,200 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 (2,128 postings), Aws (1,324 postings), Azure (1,003 postings), Rag (916 postings), Gcp (817 postings), Pytorch (655 postings), Prompt Engineering (639 postings), Claude (571 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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