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Statistical Modeling Jobs in Ohio (NOW HIRING)

This role focuses on developing and enhancing statistical and predictive models to improve forecasting accuracy, workforce planning, and operational decision‑making. You will work closely with ...

Advanced skill in statistical modeling, SQL, and database concepts required. * Demonstrated experience leading small technical teams or pods, providing mentorship and technical direction.

Advanced skill in statistical modeling, SQL, and database concepts required. * Demonstrated experience leading small technical teams or pods, providing mentorship and technical direction.

Advanced skill in statistical modeling, SQL, and database concepts required. * Demonstrated experience leading small technical teams or pods, providing mentorship and technical direction.

... statistical models for our income statement. The model-building process is holistic, and will ... The role also involves communicating modeling approaches and results to stakeholders across the ...

Lead Forecasting Engineer

Toledo, OH · On-site

$100K - $132K/yr

Your primary responsibility will be to lead the development of forecasting and statistical models for our enterprise application for manufacturers and distributors. You will work closely with the ...

Advanced skill in statistical modeling, SQL, and database concepts required.  Demonstrated experience leading small technical teams or pods, providing mentorship and technical direction.

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Statistical Modeling information

See Ohio salary details

$34.7K

$52.6K

$94.1K

How much do statistical modeling jobs pay per year?

As of Jun 10, 2026, the average yearly pay for statistical modeling in Ohio is $52,621.00, according to ZipRecruiter salary data. Most workers in this role earn between $39,900.00 and $57,000.00 per year, depending on experience, location, and employer.

What are some common challenges faced by professionals in statistical modeling roles, and how can they be managed?

Professionals in statistical modeling often encounter challenges such as dealing with incomplete or messy data, selecting the most appropriate modeling techniques, and clearly communicating complex results to non-technical stakeholders. Managing these challenges typically involves collaborating closely with data engineers and domain experts, employing robust data cleaning practices, and staying up-to-date with new statistical methods. Additionally, effective communication skills are essential for translating technical findings into actionable business insights, ensuring that modeling efforts drive real-world impact.

What is statistical modeling?

Statistical modeling is the process of using mathematical models and statistical techniques to analyze data, identify patterns, and make predictions or inferences. It involves building models that represent relationships between variables in real-world systems. These models can be used for forecasting, hypothesis testing, and decision-making in various fields such as business, science, and engineering. Statistical modeling helps turn raw data into actionable insights by quantifying uncertainty and highlighting significant trends.

What are the key skills and qualifications needed to thrive as a Statistical Modeler, and why are they important?

To excel as a Statistical Modeler, a solid background in statistics, mathematics, and data analysis—often supported by a degree in a quantitative field—is essential. Proficiency with statistical software such as R, Python, SAS, or SPSS and familiarity with data visualization tools are typically required. Strong problem-solving skills, critical thinking, and effective communication help convey complex findings to non-technical stakeholders. These skills ensure accurate model development, actionable insights, and effective decision-making based on data.

What is the difference between Statistical Modeling vs Data Analyst?

AspectStatistical ModelingData Analyst
Required CredentialsDegree in statistics, mathematics, or related field; proficiency in statistical softwareDegree in data science, statistics, or related; strong analytical skills
Work EnvironmentResearch, academia, or data-driven industries; focus on model developmentBusiness, marketing, or finance; focus on data interpretation and reporting
Employer & Industry UsageUsed in industries requiring predictive models and complex analysisUsed across various industries for data reporting and insights

Statistical Modeling involves creating mathematical models to understand data patterns and make predictions, often requiring advanced statistical knowledge. Data Analysts focus on interpreting data, generating reports, and providing actionable insights. While both roles work with data, Statistical Modeling emphasizes model development, whereas Data Analysts concentrate on data interpretation and presentation.

What are popular job titles related to Statistical Modeling jobs in Ohio? For Statistical Modeling jobs in Ohio, the most frequently searched job titles are:
What cities in Ohio are hiring for Statistical Modeling jobs? Cities in Ohio with the most Statistical Modeling job openings:
Infographic showing various Statistical Modeling job openings in Ohio as of June 2026, with employment types broken down into 1% As Needed, 92% Full Time, 5% Part Time, 1% Temporary, and 1% Contract. Highlights an 84% Physical, 3% Hybrid, and 13% Remote job distribution, with an average salary of $52,621 per year, or $25.3 per hour.
"Java/Hadoop Developer" OR "Big Data Engineer"

"Java/Hadoop Developer" OR "Big Data Engineer"

Avani Technology Solutions, Inc.

Columbus, OH • On-site

$51.25 - $66.50/hr

Contractor

Posted 13 days ago


Job description

Please find the requirement below and let me know your availability along with updated resume.
Position : Java/Hadoop Developer
Location : Columbus, Ohio
Duration : 8 Months contract with possible extension
Top Three Skills:
1. Java Developer w/ a strong understanding of Kafka
2. HBase (Apache) - NoSql database that sits over Hadoop; on prem., MapR distribution (would also look at experience w/HortonWorks or Cloudera)
3. Kafka
4. Experience w/"Containers," ideally Docker
Job Description:
Cleint is looking for a Big Data Engineer responsible for supporting Big Data analytics. Work closely with business partners to translate complex functional and technical requirements into high performing Big Data systems. Work on multiple projects as a technical lead
to develop, test, and deliver Big Data solutions.
Additional Information:
-Conducts logical and physical database design
  • Identifies unique opportunities to collect new data.
  • Designs ETL processes and data pipelines to build large, complex data sets.
  • Strategizes new uses for data and its interaction with data design.
  • Finds new uses for existing data sources.
  • Conducts statistical modeling and experiment design.
  • Discovers "stories" told by the data and presents them to business partners
  • Tests and validates predictive models.
  • Builds data visualization prototypes.
  • Implements automated processes for efficiently producing scale models.
  • Designs, modifies and builds new data processes.
  • Implement, configure, administer, monitor Hadoop clusters
  • Implements new or enhanced software designed to access and handle data more efficiently.
  • Prepare and communicate status, issues, and opportunities to the business.
  • Provides technical assistance to junior team members
  • Create, refine and enforce data management standards, policies, and procedures.
  • Evaluates emerging Big Data technologies to develops next-generation Big Data analytics framework
  • Responsible for problem escalation to appropriate L Brands teams and third parties as appropriate.
  • Provide 24x7 on-call support

AUTHORITY:
  • Recommend expenditures as required to meet Big Data support requirements.
  • Recommend the initiation of Big Data support activities and projects .
  • Recommend Big Data standards/directions/technologies.

QUALIFICATIONS:
Required:
  • 4 year degree in Information Systems or an equivalent combination of course work

and job experience
  • 4-6 years experience with Big Data technologies and analytics