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Operational Analytics Jobs in Ohio (NOW HIRING)

Equal fluency in modern AI tooling, rigorous analytical thinking, and operational context is essential. Responsibilities * AI Solution Development - Design, build, and iterate on applied AI and ...

Equal fluency in modern AI tooling, rigorous analytical thinking, and operational context is essential. Responsibilities * AI Solution Development - Design, build, and iterate on applied AI and ...

Equal fluency in modern AI tooling, rigorous analytical thinking, and operational context is essential. Responsibilities * AI Solution Development - Design, build, and iterate on applied AI and ...

Equal fluency in modern AI tooling, rigorous analytical thinking, and operational context is essential. Responsibilities * AI Solution Development - Design, build, and iterate on applied AI and ...

Operations Analysis Engineer

Dayton, OH · On-site

$65K - $89K/yr

... operational analysis (OA) efforts. This position provides an opportunity to join an elite team and enhance the performance of an organization whose primary mission is to support our nation's War ...

As a Marketing Operations Analyst on the Marketing Operations & Technology team, you'll help share ... Analytics and Reporting: Design and execute data analyses to derive actionable insights, providing ...

As a Marketing Operations Analyst on the Marketing Operations & Technology team, you'll help share ... Analytics and Reporting: Design and execute data analyses to derive actionable insights, providing ...

As a Marketing Operations Analyst on the Marketing Operations & Technology team, you'll help share ... Analytics and Reporting: Design and execute data analyses to derive actionable insights, providing ...

As a Marketing Operations Analyst on the Marketing Operations & Technology team, you'll help share ... Analytics and Reporting: Design and execute data analyses to derive actionable insights, providing ...

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As a Marketing Operations Analyst on the Marketing Operations & Technology team, you'll help share ... Analytics and Reporting: Design and execute data analyses to derive actionable insights, providing ...

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Showing results 1-20

Operational Analytics information

See Ohio salary details

$61.3K

$119.1K

$170.2K

How much do operational analytics jobs pay per year?

As of Jul 16, 2026, the average yearly pay for operational analytics in Ohio is $119,147.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,100.00 and $141,700.00 per year, depending on experience, location, and employer.

Is operation analyst a good career?

An operations analyst is a valuable role focused on analyzing data to improve business processes, often requiring skills in data analysis tools like Excel or SQL. It offers opportunities for career growth, especially with experience and certifications, and is suitable for those interested in problem-solving and process optimization.

What types of teams or departments do Operational Analytics professionals typically collaborate with?

Operational Analytics professionals frequently work cross-functionally, collaborating with departments such as supply chain, finance, production, IT, and customer service. They often serve as a bridge between data teams and operational leaders, ensuring that insights are effectively implemented to drive process improvements. This collaboration requires clear communication and a practical understanding of various business functions, making the role ideal for those who enjoy teamwork and tangible business impact. These interactions can offer excellent networking opportunities and help build a comprehensive understanding of the organization's operations, supporting both immediate project success and long-term career growth.

What jobs pay $500,000 a year in the US?

In operational analytics, senior roles such as Director of Analytics or Chief Data Officer can reach or exceed $500,000 annually, especially in large corporations or financial institutions. These positions typically require extensive experience, advanced skills in data management and visualization tools, and often involve leadership responsibilities and strategic decision-making.

What is an Operational Analytics job?

An Operational Analytics job focuses on using data to optimize business processes, improve efficiency, and drive decision-making. Professionals in this role analyze real-time and historical data to identify patterns, streamline operations, and enhance performance. They often work with cross-functional teams to implement data-driven strategies, leveraging tools like SQL, business intelligence software, and automation. The goal is to turn raw data into actionable insights that improve operational workflows and business outcomes.

What are the key skills and qualifications needed to thrive in the Operational Analytics position, and why are they important?

To excel in Operational Analytics, you need strong analytical abilities, a background in business operations or supply chain, and often a bachelor's degree in a related field such as business, engineering, or mathematics. Familiarity with data analytics tools like SQL, Excel, Tableau, or Python and certifications in data analytics or Lean Six Sigma are commonly required. Excellent problem-solving, communication, and collaboration skills help you translate data into actionable recommendations for cross-functional teams. These competencies enable you to drive operational improvements and informed decision-making within an organization.

What does an operational analyst do?

An operational analyst evaluates and improves business processes by analyzing data, identifying inefficiencies, and recommending solutions. They often use tools like Excel, SQL, or data visualization software and work closely with management to optimize operational performance.

How much do operations analysts get paid?

Operations analysts typically earn a median annual salary of around $65,000 to $75,000, depending on experience, location, and industry. Entry-level roles may start lower, while experienced analysts with specialized skills or certifications can earn over $90,000 annually.
What are the most commonly searched types of Operational Analytics jobs in Ohio? The most popular types of Operational Analytics jobs in Ohio are:
Infographic showing various Operational Analytics job openings in Ohio as of July 2026, with employment types broken down into 1% Internship, 90% Full Time, 7% Part Time, and 2% Contract. Highlights an 79% Physical, 5% Hybrid, and 16% Remote job distribution, with an average salary of $119,147 per year, or $57.3 per hour.
Applied AI Engineer

Applied AI Engineer

Cushman & Wakefield

Cincinnati, OH • On-site, Remote

Full-time

Medical, Dental, Vision, Life, Retirement

This job post has expired today. Applications are no longer accepted.


Cushman & Wakefield rating

7.5

Company rating: 7.5 out of 10

Based on 154 frontline employees who took The Breakroom Quiz

83rd of 162 rated real estate companies


Job description

Job TitleApplied AI EngineerJob Description SummaryThe Applied AI Engineer is a hands-on builder who sits at the intersection of AI engineering, operational analytics, and business process expertise. This role designs, prototypes, and operationalizes AI and analytics solutions that automate work, sharpen decision-making, and measurably improve performance across the organization.
Embedded directly with operational leaders, the Applied AI Engineer translates real-world business challenges into working proofs of concept - independently building end-to-end, including the data, modeling, and lightweight infrastructure needed to demonstrate value quickly. When solutions prove valuable, this role partners with the data engineering team to harden, scale, and operationalize them for production use.
Reporting to the Director of Advanced Analytics & AI, this position is a critical execution role within the centralized Advanced Analytics & AI team. Success requires equal fluency in modern AI tooling (including machine learning, NLP, and generative AI), rigorous analytical thinking, and the operational context needed to ensure solutions are trusted, adopted, and continuously improved. The ideal candidate combines technical depth with the business fluency needed to work effectively across stakeholders, data, and code.Job DescriptionApplied AI EngineerRole Overview

The Applied AI Engineer is a hands-on builder who sits at the intersection of AI engineering, operational analytics, and business process expertise. This role designs, prototypes, and operationalizes AI and analytics solutions that automate work, sharpen decision-making, and measurably improve performance across the organization. The Applied AI Engineer embeds directly with operational leaders to translate real-world business challenges into working proofs of concept, and partners with data engineering to harden and scale the solutions that prove valuable.

Reporting to the Director of Advanced Analytics & AI, this position is a critical execution role within the centralized Advanced Analytics & AI team. Success requires the ability to move quickly and independently during the prototype phase - building end-to-end without waiting for platform support - while also collaborating effectively with data engineering, operations, and business stakeholders to take proven solutions into production. Equal fluency in modern AI tooling, rigorous analytical thinking, and operational context is essential.

Responsibilities
  • AI Solution Development - Design, build, and iterate on applied AI and machine learning solutions - including forecasting, classification, anomaly detection, NLP, and generative AI / LLM-based workflows - with a focus on solving concrete operational problems.
  • Rapid Prototyping & Proof of Concept - Independently build end-to-end POCs to validate AI and analytics ideas quickly - including standing up the data, modeling, and lightweight infrastructure needed to demonstrate value before committing to production investment.
  • Path to Production - Partner with the data engineering team to harden, scale, and operationalize solutions that prove out: integrating them into operational systems, ensuring they are reliable and observable, and supporting iteration once deployed. Data engineering owns the platform and production pipelines; this role owns the AI/analytics solution running on them.
  • Evaluation & Measurement - Define success metrics, design offline and online evaluations, and quantify business impact. Build the feedback loops needed to detect drift, regression, or misuse and respond to them.
  • Operational Analytics & Insight - Analyze operational data, workflows, and performance trends to identify where AI and automation can deliver measurable value, and to surface actionable insights that support service delivery and efficiency.
  • Embedded Business Partnership - Work directly with Geography or Vertical leadership and frontline operators to understand workflows, decision points, and constraints. Translate operational problems into well-scoped AI and analytics solutions - and translate technical results back into clear, actionable guidance.
  • Data Preparation & Feature Engineering - Prepare, clean, and structure datasets for analytics and AI workflows. Engineer features, design retrieval strategies for LLM-based systems, and partner with data engineering on upstream data quality and pipeline needs.
  • Building on Databricks - Develop, test, and deploy analytics and AI solutions within the Databricks Lakehouse environment provided by the data engineering team. Apply software engineering practices - version control, testing, code review, modular design - so prototypes are easy to harden and solutions are easy to maintain.
  • Adoption, Change & Continuous Improvement - Partner with field and operational teams to pilot, refine, and drive adoption of AI tools. Iterate based on user feedback, evaluation results, and evolving business needs so solutions deliver compounding value over time.
  • Responsible AI Practice - Apply practical judgment around model limitations, hallucinations, bias, privacy, and human-in-the-loop design so deployed solutions are trustworthy and appropriate for the operational context.
Basic Qualifications
  • Bachelor's degree in Analytics, Data Science, Computer Science, Engineering, or a related field
  • 4-7 years of experience in analytics, data science, or AI/ML engineering, with at least 2 years building and deploying ML or AI solutions
  • Strong proficiency in Python and SQL, including writing maintainable, tested code beyond exploratory notebooks
  • Hands-on experience building applied AI or ML solutions - e.g., predictive models, NLP, or LLM-based applications - not only conceptual familiarity
  • Demonstrated ability to build end-to-end proofs of concept independently, including the data wrangling, modeling, and lightweight infrastructure needed to show value quickly
  • Experience partnering with data engineering or platform teams to take prototypes into production
  • Experience working with large datasets in modern analytics platforms such as Databricks
  • Demonstrated ability to translate operational problems into analytical and AI approaches that deliver measurable business outcomes
  • Strong communication skills with non-technical stakeholders, including the ability to make AI behavior, limitations, and results understandable
Preferred Qualifications
  • Production experience with generative AI, LLM APIs (e.g., OpenAI, Anthropic), RAG systems, or agentic workflows
  • Familiarity with MLOps tooling and practices (e.g., MLflow, model registries, CI/CD for ML, monitoring/observability)
  • Experience designing evaluation frameworks for AI systems, including offline benchmarks and online experimentation
  • Experience in operational, services, or asset-heavy environments
  • Exposure to predictive modeling, time series analysis, or NLP in business contexts
  • Familiarity with Databricks Lakehouse concepts and collaborative analytics workflows
  • Track record of driving adoption of analytics or AI tools within business operations, including process and change-management considerations
  • Ability to work independently while managing multiple concurrent initiatives

Cushman & Wakefield also provides eligible employees with an opportunity to enroll in a variety of benefit programs, generally including health, vision, and dental insurance, flexible spending accounts, health savings accounts, retirement savings plans, life, and disability insurance programs, and paid and unpaid time away from work. In addition to a comprehensive benefits package, Cushman and Wakefield provide eligible employees with competitive pay, which may vary depending on eligibility factors such as geographic location, date of hire, total hours worked, job type, business line, and applicability of collective bargaining agreements.
The compensation that will be offered to the successful candidate will depend on factors such as whether the position is covered by a collective bargaining agreement, the geographic area in which the work will be performed, market pay rates in that area, and the candidate's experience and qualifications.
The company will not pay less than minimum wage for this role.
The compensation for the position is: $ 85,000.00 - $100,000.00

C&W Services is an Equal Opportunity employer to all protected groups, including protected veterans and individuals with disabilities. Discrimination of any type will not be tolerated.

In compliance with the Americans with Disabilities Act Amendments Act (ADAAA), if you have a disability and would like to request an accommodation in order to apply for a position at C&W Services, please call the ADA line at 1-888-365-5406 or emailAccommodations@cushwake.com. Please refer to the job title and job location when you contact us.

INCO: "C&W Services"

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