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Jmp Data Analytics Jobs in Chicago, IL (NOW HIRING)

MonoSol

Senior Scientist Data Science

Chicago, IL · On-site

Bring a strong scientific lens to every analysis by ensuring methods are not only technically sound ... JMP is a plus * Deep grounding in statistical methods, including both frequentist and Bayesian ...

Collabera

Clinical Statistician

Lake Bluff, IL

Candidates strong in JMP software is also a big plus. Candidates should have a strong background in high-dimensional data analysis, preferably in genomics and biomarker research applications.

littelfuse

Sr. Debug Engineer (Chicago)

Chicago, IL · On-site

$107K - $147K/yr

Experience using data analysis tools such as Excel, Power BI, Minitab, JMP, or similar. Preferred Skills * Knowledge of Lean Manufacturing and Six Sigma principles. * Experience with automated test ...

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All JobsJmp Data Analytics JobsJmp Data Analytics Jobs in Chicago, IL

Jmp Data Analytics information

See Chicago, IL salary details

$45.8K

$133.6K

$182.9K

How much do jmp data analytics jobs pay per year?

As of Aug 27, 2026, the average yearly pay for jmp data analytics in Chicago, IL is $133,627.00, according to ZipRecruiter salary data. Most workers in this role earn between $118,000.00 and $141,600.00 per year, depending on experience, location, and employer.

What is JMP Data Analytics?

JMP Data Analytics refers to the use of the JMP software platform for statistical analysis and data visualization. JMP, developed by SAS, is widely used by scientists, engineers, and analysts to explore, analyze, and visualize data interactively. It offers tools for data cleaning, statistical modeling, and advanced analytics without requiring extensive programming knowledge. JMP is especially popular in industries such as pharmaceuticals, manufacturing, and research for its user-friendly interface and robust statistical capabilities.

How does a JMP Data Analytics professional typically collaborate with other departments within an organization?

JMP Data Analytics professionals often work closely with teams across the organization, including engineering, quality assurance, product development, and operations. They support these teams by analyzing complex data sets, creating visualizations, and providing actionable insights to guide decision-making. Effective communication and an ability to translate technical findings into clear, business-relevant recommendations are essential. Regular cross-functional meetings and collaborative projects are common, fostering a dynamic work environment where analytical expertise directly impacts company performance.

What are the key skills and qualifications needed to thrive as a JMP Data Analytics professional, and why are they important?

To thrive as a JMP Data Analytics professional, you need a solid background in statistics, data analysis, and problem-solving, often supported by a degree in a quantitative field. Proficiency with JMP software, along with familiarity with data visualization, scripting, and potentially certifications such as JMP Certified Specialist, is highly valuable. Strong communication, critical thinking, and attention to detail help you interpret results and present actionable insights effectively. These skills and qualifications are essential for transforming complex data into clear, impactful business decisions.

What is the difference between Jmp Data Analytics vs Data Analyst?

AspectJmp Data AnalyticsData Analyst
Required SkillsProficiency in JMP software, data visualization, statistical analysisData manipulation, statistical tools, Excel, SQL
Work EnvironmentResearch labs, analytics firms, industries using JMPBusiness, finance, healthcare, various industries
CertificationsJMP certification, data analysis certificationsCertified Analytics Professional, Microsoft Excel certifications

Jmp Data Analytics professionals focus on using JMP software for statistical analysis and data visualization, often within research or specialized analytics environments. Data Analysts typically work across various industries, utilizing a broader set of tools like Excel and SQL. While both roles require strong analytical skills, Jmp Data Analytics roles emphasize JMP proficiency, whereas Data Analysts may have more diverse technical toolsets.

What are popular job titles related to Jmp Data Analytics jobs in Chicago, IL?

For Jmp Data Analytics jobs in Chicago, IL, the most frequently searched job titles are:

What job categories do people searching Jmp Data Analytics jobs in Chicago, IL look for?

The top searched job categories for Jmp Data Analytics jobs in Chicago, IL are:

What cities near Chicago, IL are hiring for Jmp Data Analytics jobs?

Cities near Chicago, IL with the most Jmp Data Analytics job openings:

Jmp Data Analytics jobs near you
Infographic showing various Jmp Data Analytics job openings in Chicago, IL as of August 2026, with employment types broken down into 86% Full Time, and 14% Temporary. Highlights an 71% In-person, and 29% Remote job distribution, with an average salary of $133,627 per year, or $64.2 per hour.

Senior Scientist Data Science

MonoSol

Chicago, IL • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 17 days ago

MonoSol rating

7.9

Company rating: 7.9 out of 10

Based on 6 frontline employees who took The Breakroom Quiz

Job description

We're looking for an experienced Data Scientist with a background in materials, chemistry, polymers, or chemical engineering to transform how data drives decisions across R&D and manufacturing. You'll build advanced statistical and machine learning models, develop digital twins, and accelerate our understanding of materials, chemistry, and processes through predictive modeling and optimization. This role sits at the intersection of scientific insight, statistical rigor, and real-world impact. The ideal candidate pairs strong full-stack data science skills with domain intuition and thrives in translating complex technical problems into practical solutions.
As a senior individual contributor, you'll lead end-to-end modeling initiatives and translate insights into deployed solutions and operational recommendations that improve yield, quality, cost, and cycle time. You'll work across diverse data environments (from small, high-value R&D experiments to complex, high-dimensional production datasets) turning complexity into clear, actionable direction. Your work will directly shape how teams access, use, and trust data, helping build a more agile, innovation-focused organization.
Beyond building models, you'll help elevate our broader data science capabilities by developing reusable tools, scalable workflows, and high-quality data assets that amplify impact across projects and teams. This is an opportunity to do meaningful, technically challenging work while shaping how data science is applied in a materials and manufacturing environment.
Key Responsibilities
Scientific and Statistical Partnership
  • Partner with scientists, engineers, and manufacturing teams to frame high-impact problems, assess data quality, and apply rigorous statistical thinking to materials, process, and production challenges.
  • Bring a strong scientific lens to every analysis by ensuring methods are not only technically sound, but meaningful in the context of chemistry, materials behavior, and real-world process dynamics.

Predictive Modeling, Digital Twins, and Optimization
  • Design, build, and evolve advanced statistical and machine learning models that drive technical decision making across R&D and manufacturing.
  • Work with domain experts to support development of digital twin and hybrid models that combine first-principles knowledge with machine learning to simulate, predict, and optimize material and process performance.
  • Own models through the full lifecycle ensuring they are robust, interpretable, and actionable in operational environments.

Data Transformation and Feature Engineering
  • Work across complex, multi-source datasets spanning laboratory, pilot, and manufacturing environments, transforming raw data into structured, analysis-ready assets.
  • Engineer meaningful features that unlock insight into structure-property-process-performance relationships and improve model performance, interpretability, and usability.

Visualization, Communication, and Decision Support
  • Translate complex analyses into clear, compelling visualizations, tools, and narratives that enable teams to quickly understand and act on insights.
  • Deliver recommendations that directly influence R&D direction, process optimization, and manufacturing performance, and communicate effectively across diverse audiences.

Leadership, Capability Building & Data Advancement
  • Lead data science initiatives from problem definition through sustained use in decision-making, working across R&D and manufacturing.
  • Act as a thought leader to technical teams by shaping analytical approaches, guiding best practices, and mentoring others in statistical thinking and disciplined use of data.
  • Drive improvements in how technical data is structured, captured, and used and develop reusable tools, workflows, and codebases that scale impact beyond individual projects.

Qualifications
Education
  • Bachelor's degree in Materials Science, Chemistry, Chemical Engineering, Polymer Science, Data Science, Statistics, Computer Science, or a related technical field; Master's or PhD strongly preferred

Experience
  • 5+ years of applying data science, statistics, or advanced analytics to complex problems in materials, chemistry, manufacturing, or related technical environments
  • Track record of delivering measurable impact through modeling and analysis (e.g. improvements in yield, quality, cost, or efficiency) and owning delivery from problem framing through deployment
  • Experience with modeling across data scales and structures spanning small, high-value experimental datasets to large high-dimensional production or process datasets
  • Experience working with manufacturing, process, or production systems, and connecting analysis to real-world operational performance

Technical Skills
  • Strong proficiency in Python and modern data science tooling (e.g., pandas, NumPy, scikit-learn, PyTorch/TensorFlow, LightGBM, SHAP); familiarity with R or JMP is a plus
  • Deep grounding in statistical methods, including both frequentist and Bayesian approaches, with the ability to design experiments, quantify uncertainty, and make decisions under limited data
  • Experience developing predictive and explanatory models, including feature engineering, latent variable methods, and interpretable modeling approaches
  • Strong SQL skills and experience working with structured and relational data; familiarity with cloud-based data and analytics platforms (e.g., AWS, Azure)
  • Experience creating interactive dashboards or data applications to support decision making (e.g., Power BI, Tableau, Streamlit, or Plotly Dash)
  • Experience building and deploying models in production or operational environments, including version control (Git), reproducibility, and lifecycle management practices
  • Experience with digital twins, hybrid modeling approaches, or combining physics-based understanding (preferred) with data-driven techniques for prediction and optimization
  • Familiarity with generative AI techniques, large language models (LLMs), or retrieval-augmented generation (RAG) as applied to scientific or engineering workflows (preferred)
  • Familiarity with materials modeling data or tools (e.g., DFT, MD, CALPHAD) or adjacent scientific computing approaches (preferred)

Who you are
  • Strong communicator who can engage effectively with scientists, engineers, manufacturing teams, and leadership and translates complexity into clarity
  • Comfortable operating in ambiguous, cross-functional environments and taking ownership of high-impact problems without waiting for direction
  • Self-directed senior IC who leads through influence by shaping analytical approaches, driving alignment across teams, and raising the bar for how data is used
  • Energized by continuous learning and staying at the forefront of materials informatics, AI/ML, and scientific computing

Additional information
Applicable only to applicants applying to a position in any location with a pay disclosure requirements under state or local law:
  • The compensation range that is described below is the possible base pay compensation that the company believes in good faith that it will pay for this role at the time of posting based on job grade for the position. Individual compensation within this range is based on many factors such as years of experience etc. so the company might pay more or less than the posted range and it is understood that this range may be modified in the future.
  • In addition to base compensation, MonoSol provides a yearly incentive compensation bonus, a profit sharing bonus when eligible, a comprehensive benefits package including medical, dental, vision insurances, short term disability, long term disability, accidental death and dismemberment, term life insurance, voluntary term life insurance, transit flexible spending account (if applicable), employee assistance program, identity theft protection, 401k and paid time off (vacation and sick days).

Status: Full Time
Job Location: Hybrid
Compensation range - $130,000.00 - $155,000.00
Incentive Compensation Bonus Target - 10-15%
Paid time off amount - 15 days
CLOSING
The above statements are intended to describe the general nature and level of the work being performed by employees assigned to this position. This is not intended as an exhaustive list of all responsibilities, duties, and skills required. MonoSol, LLC reserves the right to make changes to the job description whenever necessary.
Disclaimer
As part of MonoSol, LLC's employment process, finalist candidates will be required to complete a drug test and background check prior to employment commencing. MonoSol, LLC is an equal opportunity employer. All qualified applicants will be considered without regard to race, national origin, gender, age, disability, sexual orientation, veteran status, or marital status.
Equal Opportunity Employer
This employer is required to notify all applicants of their rights pursuant to federal employment laws.
For further information, please review the Know Your Rights notice from the Department of Labor.

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