Research Scientist Remote Jobs in Illinois (US)
This page tracks remote research scientist openings that are location-eligible for Illinois.
This page tracks remote research scientist openings that are location-eligible for Illinois.
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506 Jobs
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CDC Foundation is a nonprofit organization that helps the Centers for Disease Control (CDC) build partnerships with philanthropies, corporate entities, outside groups, and individu
Role Description The CDC Foundation is working with CDC and state and local authorities to provide surge staff to support surveillance, prevention and response activities within the Overdose Data to Action (OD2A) Capacity Building Initiative program. A potential new activity in the Division of Overdose Prevention (DOP) includes the development and implementation of a national wastewater surveillance (WWS) system to detect emerging drug threats. The DOP Office of the Associate Director for Science (OADS) is looking to hire staff to complete tasks necessary to build a foundation for a national WWS system. Qualifications - A Master’s degree is required (preferably in public health or a health-related field) - Organizational skills demonstrating high attention to detail and the ability to organize multiple priorities - Strong communication skills, both written and oral - Experience working collaboratively with diverse stakeholders and engaging in strategic partnerships - Strong understanding of design and implementation of research and epidemiologic studies - Experience with data analysis and synthesizing literature - Demonstrated ability to work well independently and within teams - Experience working in a virtual environment with remote partners and teams - Proficiency in Microsoft Excel, Word, PowerPoint, Teams and Zoom Requirements - Prior experience in drug overdose epidemiology, wastewater or laboratory activities - Experience working directly with a local and state health department - Experience developing technical guidance for health departments Responsibilities - Participate in a systematic review to describe methodology currently used to measure drug consumption using wastewater samples; serve as the main liaison in DOP to staff leading this effort in the National Center for Environmental Health (NCEH) - Serve as the DOP liaison for the Association of Public Health Laboratories (APHL) community of practice on wastewater analysis for drug consumption; joining all meetings and sharing discussion with OADS and staff managing the Overdose Data to Action (OD2A) cooperative agreement - Assist APHL in development of an ethical framework for wastewater analysis for drug consumption; join meetings with APHL and serve as liaison with OADS - Assist NCEH in the development of standards and methods; participate in meetings and potentially write sections of technical guidance - Assist OADS with overall management of the wastewater project to include developing key objectives & deliverables along with timelines and parties responsible for completion Special Notes This role is involved in a dynamic public health program. As such, roles and responsibilities are subject to change as situations evolve. Roles and responsibilities listed above may be expanded upon or updated to match priorities and needs, once written approval is received by both the CDC Foundation and CDC in order to best support public health programming. All qualified applicants will receive consideration for employment and will not be discriminated against on the basis of race, color, religion, sex, national origin, age, mental or physical disabilities, veteran status, and all other characteristics protected by law. We comply with all applicable laws including E.O. 11246 and the Vietnam Era Readjustment Assistance Act of 1974 governing employment practices and do not discriminate on the basis of any unlawful criteria in accordance with 41 C.F.R. §§ 60-300.5(a)(12) and 60-741.5(a)(7). As a federal government contractor, we take affirmative action on behalf of protected veterans. The CDC Foundation is a smoke-free environment. Relocation expenses are not included. Company Description The CDC Foundation helps the Centers for Disease Control and Prevention (CDC) save and improve lives by unleashing the power of collaboration between CDC, philanthropies, corporations, organizations, and individuals to protect the health, safety and security of America and the world.
Making life better for animals, makes life better.
Role Description As the Global Regulatory Project Lead, you will be a key individual contributor at the forefront of our innovation pipeline, guiding the regulatory strategy for novel farm and companion animal products. You will serve as the dedicated regulatory expert on global project teams, shaping development from the ground up and leading direct negotiations with agencies like the U.S. Food and Drug Administration's Center for Veterinary Medicine (CVM). This role requires a strategic professional who can navigate complex agency interactions, influence cross-functional partners, and ensure our submissions in the United States (US), European Union (EU), and other first-wave countries are successful. Your Responsibilities - Guide the design and development of the global regulatory strategy for development projects, with a primary focus on CVM/FDA submissions. - Serve as the dedicated regulatory subject matter expert on development teams, representing the regulatory viewpoint and providing risk/benefit evaluations to guide project strategy. - Act as the primary point of contact for and lead direct engagements with regulatory agencies (e.g., CVM, European Medicines Agency (EMA)), including pre-submission meetings and negotiations. - Partner with R&D to develop and implement clinical trial submission plans, ensuring alignment with the overall regulatory strategy. - Collaborate with internal stakeholders to provide technical leadership on Quality, Safety, and Efficacy sections for regulatory submissions. - Proactively identify and communicate project-specific regulatory risks and opportunities to the development team and leadership. - Comply with all company local and global policies including quality frameworks, Code of Conduct, anti-discrimination, harassment, and health, safety, and environment (HSE) policies. Qualifications - A Master’s degree or higher in veterinary medicine, biology, infectious diseases, immunology, animal science, or a related field. - At least 10 years of relevant experience in the animal health industry, with direct regulatory affairs experience in veterinary pharmaceuticals. - Demonstrated experience leading direct submissions and negotiations with regulatory agencies, with a strong preference for the U.S. Food and Drug Administration's Center for Veterinary Medicine (CVM). - Proven ability to serve as the primary regulatory expert on cross-functional project teams in a global environment, with exceptional communication, negotiation, and influencing skills. Requirements - Direct regulatory experience with both farm animal and companion animal products. - Broad experience with global registration processes, particularly leading first-wave submissions in the European Union and other key markets simultaneously. - Experience navigating novel regulatory pathways for innovative products. - A strong understanding of risk assessment and risk management fundamentals. - Knowledge of Continuous Improvement methodologies (e.g., Six Sigma, Lean). Benefits - Multiple relocation packages - Two weeklong shutdowns (mid-summer and year-end) in the US (in addition to PTO) - 8-week parental leave - 9 Employee Resource Groups - Annual bonus offering - Flexible work arrangements - Up to 6% 401K matching
Leidos is an innovation company rapidly addressing the world’s most vexing challenges in national security and health.
Role Description The Intel Sector at Leidos currently has an opening for a Research Scientist to work in Fort Belvoir, VA. This is an exciting opportunity to use your experience to support the Defense Threat Reduction Agency's (DTRA) Environmental Data Enterprise (EDE). In this mission, we support the environmental modeling activities of DTRA, DoW, international partners, and private industry, with a focus on atmospheric transport and dispersion (ATD) modeling. This is a full-time remote opportunity. The successful candidate will be a subject-matter expert in atmospheric science or meteorology and will take part in research and development efforts to enhance our numerical weather prediction (NWP) and ATD capabilities. The candidate will apply their expertise by using cutting-edge artificial intelligence and machine learning techniques and best software development practices to improve current capabilities and create new state of the art techniques for the evaluation and use of environmental data. This role is pivotal in designing, developing, and deploying next-generation environmental modeling systems that are crucial for national security. - AI-Driven Model Development: Design, develop, and implement novel AI/ML methods for creating, assessing, and modifying vast amounts of meteorological data. - Advanced R&D: Conduct research on improving meteorological model inputs (e.g., planetary boundary layer, vertical mixing, ensemble forecasting) for ATD models using AI techniques to increase accuracy and efficiency. - Model Validation: Participate in research on best practices to implement and integrate verification and validation methods for NWP models for application within the ATD environment. - System & Data Integration: Explore and design new processes to assist in the intelligent selection of meteorological data based on defined Chemical, Biological, Radiological, Nuclear, and high Explosive (CBRNE) scenarios. - Data Pipeline Management: Support the ingestion, quality checking, parsing, and storage of on-demand environmental data, including ocean, surface, and upper-air observations. - Software Development: Extend, improve, and develop software that bridges the gap between research and operations, and assist in the integration of software into DoW tools. - Operational Support: Provide subject matter expertise and technical assistance on the EDE system, including monitoring system status and recommending software or hardware enhancements to streamline operations. Qualifications - Master's degree and 6 years experience or a Ph.D. and 3 years experience in Atmospheric Science, Meteorology, Data Science, Computer Science, or a related physical sciences or engineering field. - Ability to obtain and maintain a DoW security clearance. Must be a U.S. Citizen. - Proven experience in developing and applying Artificial Intelligence and Machine Learning (AI/ML) models to complex scientific problems. - Strong background in numerical weather prediction (NWP), atmospheric modeling, or a related geophysical field. - Proficiency in programming languages such as Python, R, or Java, with experience using scientific computing libraries (e.g., NumPy, SciPy, Pandas) and ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). - Experience handling and processing large scientific data formats like NetCDF, HDF5, and GRIB. - Familiarity with data assimilation techniques and ensemble forecasting methods. - Strong analytical and problem-solving skills, with a demonstrated ability to conduct independent research and develop innovative solutions. Preferred Qualifications - Experience with atmospheric transport and dispersion (ATD) models (e.g., HPAC, SCIPUFF). - Familiarity with DoD cybersecurity practices and information assurance standards. - Experience working in a Linux/Unix environment. - Knowledge of space weather and its impact on terrestrial systems. - Experience with deploying and maintaining operational scientific models or software. Pay Range Pay Range $107,900.00 - $195,050.00. The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.
Innodata (NASDAQ: INOD) is a leading data engineering company. With more than 2,000 customers and operations in 13 cities around the world, we are an AI technology solutions provider-of-choice for 4 out of 5 of the world’s biggest technology companies, as well as leading companies across financial services, insurance, technology, law, and medicine. By combining advanced machine learning and artificial intelligence (ML/AI) technologies, a global workforce of subject matter experts, and a high-security infrastructure, we’re helping usher in the promise of AI. Our global workforce includes over 7,000 employees in the United States, Canada, United Kingdom, the Philippines, India, Sri Lanka, Israel and Germany. We’re poised for a period of explosive growth over the next few years.
Role Description Innodata is expanding its GenAI research capability to advance state-of-the-art evaluation and post-training methods for LLM and multimodal systems. As an Applied Research Scientist, LLM Evaluation & Post-Training, you will lead research and experimentation on how evaluation design, measurement strategies, and feedback signals influence model improvement. This role is ideal for a technically rigorous researcher who is deeply fluent in modern LLM evaluation and post-training, and who can turn research insight into practical methods for customer solutions and internal platform innovation. You will work across human-in-the-loop and AI-augmented workflows, partnering with Language Data Scientists and AI/ML Research Engineers to design and validate evaluation frameworks that drive measurable model gains. The ideal candidate combines strong experimental and statistical judgment with hands-on technical ability and can engage as a peer with research and engineering stakeholders at leading AI companies. What You’ll Own - Define the next generation of evaluation-driven model improvement workflows. - Study how different evaluation approaches (human, automated, hybrid) shape model selection and post-training outcomes. - Design experiments that produce credible, actionable conclusions. - Design benchmark datasets, develop evaluation taxonomies and protocols, define metrics and scoring methodologies, analyze failure modes, and test how changes in evaluation setup affect downstream fine-tuning results. - Support customer engagements by bringing scientific rigor to evaluation strategy, methodology review, and technical recommendations. - Define and execute a research agenda focused on LLM evaluation and post-training, especially evaluation-driven model improvement. - Design rigorous experiments to study how evaluation methodologies impact fine-tuning and post-training outcomes. - Develop and validate evaluation frameworks for LLM and multimodal systems, including: - benchmark/task design - scoring methods - judge/model-assisted evaluation - human evaluation protocols - robustness/stress testing - Lead research on advanced evaluation domains, including long-context, cross-modal, and dynamic multi-turn evaluations. - Study the effectiveness and limitations of existing evaluation techniques, and propose improved methodologies with clear validity and scalability tradeoffs. - Analyze model behavior and failure patterns; generate actionable recommendations for model improvement and evaluation redesign. - Collaborate with AI/ML Research Engineers to translate research methods into scalable evaluation and post-training pipelines. - Collaborate with Language Data Scientists to integrate human-in-the-loop and synthetic data/evaluation strategies into research programs. - Engage with customer technical stakeholders to understand evaluation goals, review methodologies, and provide expert recommendations. - Contribute to internal benchmark datasets, evaluation frameworks, and reusable research assets. - Produce high-quality technical documentation, internal research reports, and client-facing materials explaining methods, results, assumptions, and limitations. - Contribute to thought leadership and best practices in LLM evaluation, post-training, and GenAI quality measurement. Qualifications - MS/PhD in Computer Science, Machine Learning, Statistics, Applied Mathematics, AI, or a related quantitative scientific field (PhD strongly preferred). - 5+ years of relevant experience in applied research / research science in ML/AI, with substantial work in LLMs or foundation models. - Demonstrated experience with LLM evaluation, benchmarking, alignment, post-training, or model quality research. - Strong foundation in experimental design, statistical analysis, and scientific reasoning for ML systems. - Strong coding skills in Python for research experimentation and analysis (e.g., data processing, evaluation pipelines, statistical analysis, visualization). - Experience working with modern ML tooling/frameworks (e.g., PyTorch, Hugging Face, JAX/TensorFlow as applicable) sufficient to design and execute model/evaluation experiments. - Ability to evaluate and compare human and automated evaluation methods, including tradeoffs in cost, reliability, validity, and scalability. - Experience designing evaluation studies and protocols that are reproducible across datasets, model versions, and evaluation runs. - Ability to collaborate directly with technical stakeholders including research scientists, ML engineers, data scientists, and customer technical counterparts. - Strong communication skills and ability to present nuanced technical conclusions, assumptions, and limitations clearly. Requirements - The expected salary range for this position is $175,000 – $225,000 USD per year, based on experience, skills, and qualifications. Company Description Innodata (Nasdaq: INOD) is a global data engineering company. We believe that data and Artificial Intelligence (AI) are inextricably linked. Our mission is to enable the responsible advancement of artificial intelligence by providing the data, evaluation frameworks, and human expertise required to build AI systems that can be trusted at scale. We provide a range of transferable solutions, platforms, and services for Generative AI / AI builders and adopters. In every relationship, we honor our 36+ year legacy delivering the highest quality data and outstanding outcomes for our customers.
Advancing Evidence. Improving Lives.
• Manage large, complex research and evaluation projects focused on community safety, violence prevention, and related systems-change efforts. • Anticipate project risks and develop mitigation strategies to ensure timely, high quality deliverables. • Ensure compliance with ethical standards, IRB requirements, and data governance policies. • Lead and contribute to proposals and capture efforts for federal, state, local, foundation, and other client opportunities related to community safety. • Develop competitive proposal strategies, including conceptual design, methodological plans, staffing, and budgets. • Identify new business opportunities and cultivate partnerships that advance the organization’s mission. • Serve as a senior methodological leader, advising teams on rigorous quantitative and/or qualitative approaches. • Lead the review, analysis, synthesis, and visualization of data using appropriate practices and techniques. • Ensure data integrity, reproducibility, and strong documentation across all analytic workflows. • Translate complex research findings—both orally and in writing—into actionable insights tailored to policymakers, practitioners, and community partners. • Manage client and stakeholder relationships with professionalism and awareness of the broader policy and practice landscape. • Cultivate external relationships with researchers, practitioners, community partners, and other leaders working across the community safety and prevention landscape. • Manage and mentor staff to build technical capacity in community safety, prevention science, research design, and client service. • Provide thought partnership and coaching to mid level researchers on research design, analysis, and dissemination. • Model inclusive leadership practices and foster a collaborative team environment.
• Formulates and leads/co-leads novel projects with team or enables matrix collaboration on project/technology solutions to achieve creative results for impact on BR goals • Generates innovative ideas within own team and/or project team/functional community to meet new technical requirements and/or answer project key scientific/technical/development questions • Establishes target dates and priorities to enable data-driven advancements in project teams, within own team, and with collaborators, or within functional community • Oversees the progress of the study and for ensuring that the study is conducted, recorded and reported according to the study protocol • Ensures that the study is compliant with the appropriate GLP regulations, Novartis animal welfare policies, CRO in-house standard operating procedures, Novartis expert recommendations (where feasible) and all relevant international regulatory guidelines/regulations
Only applicants currently, and in the future, eligible to work in the United States will be considered for this position.
Role Description The Modeling Scientist is responsible for improving model traceability, uncertainty quantification, and predictive trustworthiness in Arva’s ecosystem model predictions. This role is central to advancing Arva’s monitoring, reporting, and verification platform for greenhouse gas emission reductions and removals. Working at the intersection of statistics, machine learning, and process-based ecosystem modeling, this role works closely with ecosystem modelers and data engineers to design robust model traceability and uncertainty frameworks that support transparent, decision-ready outputs for customers, partners, and environmental markets. The Modeling Scientist plays a critical role in translating scientific rigor into real-world impact through credible, auditable modeling systems. Qualifications - 5+ years demonstrated experience in uncertainty quantification, probabilistic modeling, and data model integration - Master’s or PhD degree or equivalent experience in Statistics, Applied Mathematics, Environmental Science, Earth System Science, Biology, or a related quantitative field - Advanced proficiency in Python and scientific computing, with experience building reproducible modeling pipelines - Strong software engineering practices, including writing modular, testable, and well-documented code - Deep commitment to scientific rigor, transparency, and integrity - Experience integrating machine learning with process-based or mechanistic models preferred - Familiarity with ecosystem or Earth system models such as DayCent or CESM preferred - Familiarity with cloud platforms and data systems, including AWS and relational or spatial databases, preferred Requirements - Generate and apply a model traceability framework for ecosystem and biogeochemical models to enable rigorous model testing and improvements. - Design and implement an uncertainty quantification framework, including parameter, structural, aleatory, and epistemic uncertainties. - Apply sensitivity analysis, multivariate testing, and cross-validation to evaluate model robustness and generalizability. - Quantify and communicate model confidence, uncertainty bounds, and performance metrics. - Develop hierarchical and Bayesian approaches for distributed and iterative model optimization. - Apply probabilistic methods to integrate data, models, and uncertainty across scenarios. - Analyze model outputs to diagnose limitations and inform model improvement strategies. - Integrate machine learning techniques with process-based models to improve predictive performance. - Partner with data engineers to implement reproducible, scalable modeling pipelines. - Contribute to the design of model evaluation and optimization workflows. - Communicate uncertainty, confidence intervals, and model performance clearly to stakeholders. - Contribute to scientific reports, model documentation, and peer-reviewed publications. - Support defensible, auditable model outputs for regulatory and credit market review. Benefits - $100k - $160k base salary Company Description Only applicants currently, and in the future, eligible to work in the United States will be considered for this position.
Advancing Evidence. Improving Lives.
• Manage day-to-day project operations in roles such as principal investigator, project director, or task lead, ensuring deliverables are completed on time, within budget, and to a high standard. • Lead collaborative project teams by developing timelines, coordinating staff assignments. • Identify research problems and design rigorous applied studies, including aligned research questions, methodologies, and analytic plans. • Apply subject-matter expertise to design and implement relevant, responsive, and impactful research and technical assistance projects. • Develop study designs with aligned research questions, methodologies, and analytic plans. • Lead and contribute to proposals for federal, state, foundation, and other clients. • Devise and implement innovative solutions to practical challenges in applied research. • Lead data collection and analysis efforts, including the design of qualitative and/or quantitative data collection tools (e.g., interview protocols, focus group guides, surveys). • Supervise field-based data collection activities, including interviews, observations, focus groups, and document reviews. • Conduct or oversee data analysis using appropriate tools and techniques for various data types. • Communicate study progress and findings clearly and effectively through reports, briefs, visualizations, and other materials. • Represent the organization professionally in client interactions and manage client and stakeholder relationships with awareness of the broader policy and practice landscape. • Communicate effectively, both orally and in writing, with clients, partners, and stakeholders, and foster positive, collaborative working relationships. • Contribute thoughtfully and creatively to project teams.
Fresenius Kabi is a global healthcare company committed to providing lifesaving technologies and medicines for infusion, clinical nutrition, and transfusion. Dr
Title: Associate Research Scientist (Cell & Gene Therapy) Location: Lake Zurich, IL Full time Job Description: Job Summary The Associate Research Scientist plans, executes and analyzes experiments in cell and gene therapy manufacturing. Collaborates with both internal and external stakeholders in advancing pipeline. Salary Range: Job Posting Range: $95,000 - $105,000 • Position is eligible to participate in a bonus plan with a target of 6% of the base salary (include only if applicable to the grade level) • Final pay determinations will depend on various factors, including, but not limited to experience level, education, knowledge, skills, and abilities. • Our benefits and programs are comprehensive and thoughtfully crafted to ensure our colleagues live healthy lives and have support when it matters most. Benefits offered include a 401(k) plan with company contributions, paid vacation, holiday and personal days, employee assistance program, and health benefits to include medical, prescription drug, dental and vision coverage. Hybrid role: Onsite 3 days per week Applicants must be authorized to work for ANY employer in the United States. Fresenius Kabi is unable to sponsor or take over sponsorship of an employment visa either now or in the future. Responsibilities - Design, execute, and analyze complex experiments related to cell and gene therapy manufacturing processes. - Develop and optimize cell culture and purification processes for clinical and commercial manufacturing. - Collaborate effectively with cross-functional teams, including R&D, engineering, product management, and quality control, to ensure project success. - Maintain detailed experimental records and generate comprehensive reports to communicate findings. - Proactively identify and troubleshoot technical challenges, implementing innovative solutions to overcome obstacles. - Stay abreast of the latest advancements in cell and gene therapy manufacturing technologies and industry trends. - Operates within Fresenius Kabi Good Documentation and Good Laboratory Practices This job position within the Business Unit – Transfusion and Cell Technologies (BU-TCT) of Fresenius Kabi USA hereby commits itself to protect any persons working under its control from work related hazards to health and safety as well as to protect the environment as the basis of life. This includes the prevention of diseases, incidents, and pollution as well as the responsible and sustainable use of resources. Our aim is to enhance our performance in the area of occupational and environmental safety, and to fulfill compliance obligations. To achieve this target, we implement and continuously improve the integrated management system according to ISO 14001 (Environmental Management System, or EMS) and ISO 45001 (Occupational Health and Safety Management Systems, or OHSMS). Requirements The requirements listed below are representative of the knowledge, skill, and /or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. • Ph.D. with 1+ years of relevant experience, M.S. degree with 2+ years of relevant experience, or B.S. degree in Engineering (Biomedical, Biochemical, Mechanical, Systems, or similar) or Biology with 3+ years of relevant experience. • Experience in cell culture, aseptic technique, and cellular analysis methods (such as flow cytometry, microscopy, ELISA, etc.). • Proven track record of written publications and/or oral presentations. • Strong analytical skills. • Demonstrated leadership and project management abilities. • Self-motivated and capable of working independently. • Excellent verbal and written communication skills. • Willingness to travel up to 10%. Additional Information We offer an excellent salary and benefits package including medical, dental and vision coverage, as well as life insurance, disability, 401K with company contribution, and wellness program. Please note that joining our team does not create a guaranteed or permanent employment arrangement. All employment is at‑will, meaning both the employee and Fresenius Kabi have the right to end the employment relationship at any time, in accordance with applicable federal and state laws. Fresenius Kabi is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, citizenship, immigration status, disabilities, or protected veteran status.
Role Description As part of the Thermo Fisher Scientific team, you’ll discover meaningful work that makes a positive impact on a global scale. Join our colleagues in bringing our Mission to life every single day to enable our customers to make the world healthier, cleaner and safer. We provide our global teams with the resources needed to achieve individual career goals while helping to take science a step beyond by developing solutions for some of the world’s toughest challenges, like protecting the environment, making sure our food is safe or helping find cures for cancer. As a Field Applications Scientist, you will provide technical support and training for our Olink proteomics product portfolio. You'll serve as a scientific advisor, helping customers optimize their workflows and maximize the value of their investments while contributing to our mission of making the world healthier, cleaner, and safer. This is a remote role based in the Boston, MA area. Please note that relocation assistance is not provided for this position. A Day in the Life: - Provide technical support and training for the Olink proteomics product portfolio - Collaborate with sales teams and customers to deliver product demonstrations and applications support and training that enables research and innovation - Deliver both pre- and post-sales technical expertise across multiple technology platforms - Develop new applications and troubleshoot complex technical issues - Build and maintain strong relationships with customers and internal stakeholders - Partner cross-functionally with sales, marketing, R&D, and product management teams to ensure customer success and drive business growth through technical excellence. Qualifications - Bachelor’s degree in Chemistry, Biochemistry, Molecular Biology, or related field with 5+ years of relevant experience; Advanced degree with 3+ years of relevant experience - Demonstrated expertise in method development and technical problem-solving - Clear written and verbal communication skills with ability to explain complex concepts to diverse audiences - Strong presentation and training capabilities for both technical and non-technical audiences - Ability to work independently and collaboratively in a results-oriented environment - Experience in project management and ability to handle multiple priorities - Customer service orientation and interpersonal skills - Ability to build and maintain effective relationships with internal teams and external customers - Willingness to travel up to 25-50% Requirements - Must be legally authorized to work in the United States without sponsorship now or in the future - Must be able to pass a comprehensive background check and drug screen Benefits - The salary range estimated for this position based in Massachusetts is $83,300.00–$130,000.00. - This position may also be eligible to receive a variable annual bonus based on company, team, and/or individual performance results in accordance with company policy. - A choice of national medical and dental plans, and a national vision plan, including health incentive programs - Employee assistance and family support programs, including commuter benefits and tuition reimbursement - At least 120 hours paid time off (PTO), 10 paid holidays annually, paid parental leave (3 weeks for bonding and 8 weeks for caregiver leave), accident and life insurance, and short- and long-term disability in accordance with company policy - Retirement and savings programs, such as our competitive 401(k) U.S. retirement savings plan - Employees’ Stock Purchase Plan (ESPP) offers eligible colleagues the opportunity to purchase company stock at a discount
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R, Python, AI/ML, AI, Observability/Monitoring, TensorFlow