Interested in this Research Scientist role at Oil-Dri Corporation of America?
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Role Overview
This unique role within the Oil\-Dri R\&D team reports to the VP of R\&D and requires a combination of technical strength with the desire to commercialize innovation. While supporting growth \& innovation focus, this role also involves operational execution. This technical role will support innovation advancement by rapidly researching and evaluating a variety of new to world and new to Oil\-Dri ideas at the bench.
This is an exciting opportunity for the right individual to leverage their technical expertise and drive Oil\-Dri expansion and position us to capture national and global opportunities in a timely manner.
Role based out at the Innovation Campus (Vernon Hills, IL). Monday \- Friday onsite required.
Key Responsibilities
- Conduct independent research and/or development work on major research projects
- Support growth and innovation strategy execution aligned with overall Oil\-Dri business goals.
- Partner with teammates to contribute to innovation portfolio and roadmap to drive growth and investment.
- Expected to play an active role in contributing to the creation of new products and supporting existing products
- Plans, designs, and implements projects under the framework of a loosely defined idea or problem
- Demonstrates an ability to draw non\-obvious conclusions and make recommendations for new or modified paths of progression
- Provides solutions to complex problems requiring innovation in methodology
- Expected to recognize and recommend new ideas of commercial importance within his/her area of expertise
- Maintains a high level of competence through an up\-to\-date awareness of emerging technologies like AI
Qualifications
Education \& Experience:
- M.S degree with 3 – 5 years or B.S. degree in Chemistry, Biochemistry or Chemical Engineering with 5 – 7 years’ work experience
- A passion for innovation and commercializing innovation with examples of prior contributions to growth and delivering results.
Skills \& Abilities:
- Record of providing technical solutions to complex problems where little precedent exists using ingenuity, creativity, and scientific approach
- Demonstrated capacity for independent, innovative, proactive approach to research and/or process improvement, but comfortable working in a team environment
- Capacity for making major decisions in the creation, planning, execution, and interpretation of technical data
- An individual in this on\-site position will have the right blend of technical expertise, business acumen and passion for innovation execution.
- Curiosity related to potential markets that line up well with product innovation ideas and willingness and ability to research market trends and opportunities themselves
- Comfortable with diverse responsibilities and multiple project assignments with the ability to work through ambiguity and generate clarity
- Possess good working knowledge of research principles, theories, and techniques, with specialization in at least one field (chemistry, biochemistry, engineering)
- Excellent written and oral communication skills
- Mastery of word processing, spreadsheets, and graphics and AI awareness
- Ability to lift up to 30 lbs. and to travel approximately 10% of the time.
Compensation \& Benefits
- Competitive pay ($76,855 \- $99,911\) \+ annual bonus
- 401(k) with 6% company match
- Paid parental leave, generous PTO, \& paid holidays
- Work\-life balance
- Career growth with exposure to senior leadership.
- Annual merit increase opportunity
- Fitness \& Gym Reimbursement
- Employer Contribution \- Health, Dental
About Us
Oil\-Dri Corporation of America is a leading manufacturer and supplier of specialty sorbent products for consumer and business\-to\-business markets that has been voted as a Top 100 workplaces in the Chicago Tribune. Oil\-Dri’s products are sold in the pet care, animal health, fluids purification, agricultural, sports field, industrial and automotive markets. Oil\-Dri controls millions of tons of specialty mineral reserves, including calcium bentonite, attapulgite, and diatomaceous shale. The company’s mines and manufacturing facilities are located in Georgia, Mississippi, Illinois, and California. Oil\-Dri is a family\-controlled and operated organization that emphasizes honesty, integrity, and accountability. The company is dedicated to fulfilling its mission to Create Value From Sorbent Minerals.
Oil\-Dri is committed to providing equal opportunity for all teammates and qualified candidates without regard to race, color, creed, religion, sex, age, sexual orientation, national origin, ancestry, citizenship, marital status, mental or physical disability, veteran status, or any other characteristic protected by federal, state, or local laws. Accordingly, all employment decisions and personnel actions or programs such as hiring, promotion, discipline, compensation, benefits, transfers, reductions in workforce, and training, etc. will be consistent with the principle of equal employment opportunity.
Salary Context
This $76K-$99K range is in the lower quartile for Research Scientist roles in our dataset (median: $183K across 109 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 3,823 AI roles we're tracking, Research Scientist positions make up 3% of the market. At Oil-Dri Corporation of America, 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. This role's midpoint ($88K) sits 60% below the category median. Disclosed range: $76K to $99K.
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.
Oil-Dri Corporation of America AI Hiring
Oil-Dri Corporation of America has 1 open AI role right now. They're hiring across Research Scientist. Based in Vernon Hills, IL, US. Compensation range: $99K - $99K.
Location Context
Across all AI roles, 15% (590 positions) offer remote work, while 3,217 require on-site attendance. Top AI hiring metros: New York (2,643 roles, $211,000 median); San Francisco (2,168 roles, $253,000 median); Los Angeles (1,792 roles, $191,580 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 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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