ZipRecruiter

Log In

1

Applied Statistics Jobs in Madison, WI (NOW HIRING)

The Weather Channel

Senior Data Scientist

Madison, WI · On-site

MS in Applied Statistics, Mathematics, Econometrics, or other discipline related to Time-Series Analysis, Machine learning and Forecasting, or other related discipline. * 3-5 years of relevant ...

Wisconsin

Data Scientist II or III

Madison, WI

$85K/yr

At least five years of relevant experience in health-related applied research, statistics, and analytics. * Advanced proficiency with statistical software and programming languages, specifically ...

SLIPSTREAM GROUP INC

Senior Researcher

Madison, WI

Understanding of applied research methods, including research design, data collection, basic statistical concepts, and interpretation of results to produce rigorous, actionable findings. * Experience ...

Slipstream Group, Inc.

Senior Researcher

Madison, WI · On-site +1

$75K - $105K/yr

Understanding of applied research methods, including research design, data collection, basic statistical concepts, and interpretation of results to produce rigorous, actionable findings. * Experience ...

Illumina, Inc.

Sr Biochemistry Scientist

Madison, WI · On-site

$92K - $126K/yr

We want your talent, genuine curiosity about applied science, enthusiasm for creative problem ... Perform data processing, statistical evaluation, and interpretation of experimental results.

All JobsApplied Statistics JobsApplied Statistics Jobs in Madison, WI

Applied Statistics information

See Madison, WI salary details

$40.8K

$84.3K

$117.9K

How much do applied statistics jobs pay per year?

As of Aug 9, 2026, the average yearly pay for applied statistics in Madison, WI is $84,295.00, according to ZipRecruiter salary data. Most workers in this role earn between $57,400.00 and $116,900.00 per year, depending on experience, location, and employer.

What does an applied statistics do?

Professionals in Applied Statistics can expect to work on projects involving data collection, cleaning, statistical modeling, and interpretation of results for practical applications in fields like healthcare, finance, marketing, or engineering. Daily responsibilities may include designing experiments or surveys, performing hypothesis testing, and creating actionable reports or presentations for non-technical audiences. Collaboration with multidisciplinary teams—such as data scientists, subject matter experts, and business leaders—is common to ensure data-driven solutions align with organizational goals. This diversity of tasks provides valuable learning experiences and opportunities for career growth into roles such as senior analyst, data scientist, or statistical consultant.

What is an applied statistics?

An Applied Statistics job involves using statistical methods and data analysis techniques to solve real-world problems across various industries. Professionals in this field apply mathematical models, statistical software, and analytical reasoning to interpret data, make informed decisions, and optimize processes. They often work in sectors like healthcare, finance, marketing, and technology, providing insights and recommendations based on data trends.

Is applied statistics a good career?

Applied statistics is a strong career choice for those interested in data analysis, modeling, and decision-making, often requiring skills in programming languages like R or Python. It offers diverse opportunities across industries such as healthcare, finance, and technology, with competitive salaries and growth potential. Success typically depends on strong analytical skills, statistical knowledge, and the ability to communicate findings effectively.

What can you do with an applied statistics degree?

An applied statistics degree prepares individuals for roles such as data analyst, statistician, or data scientist, involving data collection, analysis, and interpretation using tools like R or Python. Graduates can work in industries like healthcare, finance, marketing, or technology, often requiring strong analytical skills and knowledge of statistical methods. Certifications in data analysis or machine learning can enhance job prospects.

What are the key skills and qualifications needed to thrive in applied statistics?

To thrive in Applied Statistics, you need a solid background in statistical theory, data analysis, and mathematical modeling, typically with a degree in statistics, mathematics, or a related field. Familiarity with statistical software such as R, SAS, Python, or SPSS, and often certifications in analytics or data science, is important. Strong analytical thinking, effective communication, and problem-solving abilities help set candidates apart. These skills ensure accurate analysis of complex data, meaningful interpretation for stakeholders, and valuable contributions to evidence-based decision making.

What are popular job titles related to Applied Statistics jobs in Madison, WI? For Applied Statistics jobs in Madison, WI, the most frequently searched job titles are:
What job categories do people searching Applied Statistics jobs in Madison, WI look for? The top searched job categories for Applied Statistics jobs in Madison, WI are:
Applied Statistics jobs near you
Infographic showing various Applied Statistics job openings in Madison, WI as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $84,295 per year, or $40.5 per hour.

Senior Data Scientist

The Weather Channel

Madison, WI

Full-time

Re-posted 9 days ago

Job description

Company Description

The Weather Company provides the best weather insight in the world, and is leading the charge in the growing area of weather decision support for business. We are offering you a unique opportunity to apply and/or develop your mathematical modeling skills on our unique set of weather data. Working with weather data is really unique and amazing; weather is in perpetual evolution, generates petabytes of new data every month, and deeply impacts people and businesses on various timescales. We serve a wide variety of businesses including renewable energies, energy traders, utility companies, insurance, retailers, and consumer product groups. As a consequence you will apply and/or learn a wide variety of statistical techniques including time series analysis, high dimensional clustering, machine learning, data mining and Bayesian modeling.

Job Description

Are you interested in applying machine learning or data mining on problems that truly improve people's life? We're looking for a mathematician/data scientist eager to tackle unique challenges in the realm of predicting weather's impact on business. You will work on a skilled team of passionate data scientists and meteorologists. Examples of projects you may encounter would be anything from predicting the electricity output of a solar park in Arizona, to predicting how much ice cream is going to be sold next week in Chicago.

  • Partner collaboratively with the business and project teams to accomplish tasks/milestones/goals.

  • Research, recommend, and implement statistical post process correction techniques using proprietary forecasts.

  • Demonstrate solutions by developing documentation, flowcharts, layouts, diagrams, charts, etc.

  • Improve operations by conducting systems analysis; recommending changes in policy and procedures.

  • Provide estimates of work effort and impact of projects and tasks, and provide team leadership, as required.

  • Continuously build your knowledge by studying new scientific methodologies and techniques.

  • Play an active role in the product requirements process, giving feedback to product management when challenges arise.

Qualifications

  • MS in Applied Statistics, Mathematics, Econometrics, or other discipline related to Time-Series Analysis, Machine learning and Forecasting, or other related discipline.

  • 3-5 years of relevant professional experience, with demonstrated achievements.

  • Can demonstrate mastery of general scientific computing softwares such as R, MATLAB, Octave, etc.

  • Experience using/implementing non-parametric regression such as  Neural Net, SVM, Random Forest, Projection Pursuit, MARS, Radial Basis Functions, AdaBoost, GLM

  • Experience in Predictive Modeling including Non-Parametric Regression, Bayesian Inference, Hidden Markov Models, Generalized ARMA, or Kalman Filtering is a plus.

  • Experience in non-linear optimisation including Simulated Annealing, Genetic Algorithm, Agent Based Modeling, Particle Swarm, Bee Colony is a plus but not necessary.

  • Knowledge of ensemble learning techniques and probabilistic forecasts is a plus.

  • Programming capabilities including C++, Java, Python is a plus but not necessary.

Additional Information


Apply