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Operations Research Analyst Jobs in Delaware (NOW HIRING)

... the daily operations of the Statewide Benefits Office. Essential Functions Professional human ... Conducts research which includes collecting, analyzing and interpreting a variety of data and ...

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Operations Research Analyst information

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$43.5K

$102.5K

$136.1K

How much do operations research analyst jobs pay per year?

As of Sep 2, 2026, the average yearly pay for operations research analyst in Delaware is $102,550.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,600.00 and $116,600.00 per year, depending on experience, location, and employer.

What is an operations research analyst?

An operations research analyst works with a company to analyze relevant data to improve business operations. Their primary duties involve setting goals, identifying potential problems, gathering pertinent information, and then using a variety of analytical methods to come up with solutions. The job requires strong analytical skills as well as the ability to think critically. Additional qualifications include a minimum of a bachelor’s degree in operations research or management science, although many employers prefer a master’s degree. Those interested in a career as an operations research analyst must have research experience in an office setting.

What are the key skills and qualifications needed to thrive as an operations research analyst?

To thrive as an Operations Research Analyst, you need strong analytical, mathematical, and problem-solving skills, typically supported by a degree in operations research, mathematics, engineering, or a related field. Proficiency with statistical analysis software, optimization tools like CPLEX or Gurobi, and programming languages such as Python or R is commonly required. Effective communication, critical thinking, and collaboration skills help translate complex data into actionable recommendations for stakeholders. These abilities are crucial for delivering data-driven solutions that improve organizational efficiency and decision-making.

What are some common challenges operations research analysts face when translating analytical findings into actionable business strategies?

Operations Research Analysts often encounter challenges in communicating complex quantitative findings to stakeholders who may not have technical backgrounds. Bridging the gap between advanced mathematical models and practical business decisions requires strong communication skills and a deep understanding of the organization's objectives. Additionally, analysts may face resistance to change when proposing new, data-driven strategies, so being able to justify recommendations with clear, accessible insights is crucial. Collaborating closely with cross-functional teams helps ensure solutions are both technically sound and aligned with operational realities.

What is the difference between Operations Research Analyst vs Data Analyst?

AspectOperations Research AnalystData Analyst
Required CredentialsBachelor's degree in operations research, mathematics, or related field; often certifications in analytics or optimizationBachelor's degree in statistics, mathematics, or related field; certifications in data analysis or visualization
Work EnvironmentCorporate, government, or consulting firms focusing on optimization and decision-makingBusiness, marketing, finance, or healthcare sectors analyzing data trends
Employer & Industry UsageOrganizations seeking to improve operational efficiency and decision processesCompanies aiming to interpret data for strategic insights and reporting

Operations Research Analysts focus on optimizing complex systems and decision-making processes using mathematical models, while Data Analysts interpret data to identify trends and support business decisions. Both roles require analytical skills and often similar educational backgrounds, but their core functions differ in scope and application.

How much do operations research analysts make?

Operations research analysts in New York City typically earn a median annual salary of around $85,000 to $100,000, depending on experience and industry. Salaries can vary based on factors such as education, certifications, and the complexity of projects handled. The role often requires strong analytical skills and proficiency with tools like optimization software and statistical analysis programs.

What are the most commonly searched types of Operations Research Analyst jobs in Delaware?

The most popular types of Operations Research Analyst jobs in Delaware are:

What are popular job titles related to Operations Research Analyst jobs in DE?

For Operations Research Analyst jobs in DE, the most frequently searched job titles are:

Infographic showing various Operations Research Analyst job openings in Delaware as of August 2026, with employment types broken down into 83% Full Time, 14% Part Time, 1% Temporary, 1% Contract, and 1% Nights. Highlights an 93% Physical, 3% Hybrid, and 4% Remote job distribution, with an average salary of $102,550 per year, or $49.3 per hour.

Quant Analytics Senior Associate - Card Data Analytics

JPMorgan Chase & Co.

Wilmington, DE • On-site

$110 - $160/hr

Other

Re-posted 11 days ago


JPMorgan Chase & Co. rating

8.0

Company rating: 8.0 out of 10

Based on 499 frontline employees who took The Breakroom Quiz

72nd of 174 rated banks


Job description

Job Summary

You’ll join the Card Data & Analytics team, a strategic partner to the Card organization using data and analytics to accelerate growth, improve campaign performance, and deliver actionable insights. In this role, you’ll work closely with stakeholders to enable informed, data-driven decisions and continuous improvement across the Chase Card portfolio.

As a Quantitative Analytics Senior Associate at JPMorganChase within the Card Data & Analytics organization, you will leverage your analytical expertise to guide strategic decisions through executive dashboards, ongoing reporting, and deep-dive analyses that address emerging business challenges. You will assess portfolio performance to uncover optimization opportunities and translate customer behavioral data—including spend, payment, and engagement patterns—to insights that shape marketing strategies and enhance card profitability through targeted campaigns and product innovations. You’ll collaborate across marketing, product, finance, and risk to turn complex analyses into clear recommendations that influence resource allocation, campaign strategy, and portfolio management.

Job responsibilities
  • Manage and analyze large, complex datasets from multiple sources to develop actionable business strategies and insights that drive measurable outcomes

  • Apply advanced analytical and data mining techniques to identify meaningful patterns and correlations within datasets, translating findings into behavioral insights that inform business decisions

  • Communicate complex analytical results clearly and effectively to business partners and senior leadership, tailoring presentations to diverse audiences and technical backgrounds

  • Conduct sophisticated analysis and deliver tactical and strategic insights across marketing, finance, and business functions using modern visualization and reporting tools

  • Serve as a subject matter expert for data-driven decision-making and opportunity identification, providing guidance on analytical approaches and methodologies

  • Partner with internal and external clients to solve quantitative business problems, optimize performance, and deliver solutions that address critical business needs

  • Align with data owners and department managers to contribute to the development of data models, analytics architecture, and enterprise-wide data strategies

  • Identify opportunities for process improvement, assess data quality, recognize statistical anomalies, and connect data findings to business processes to enhance operational efficiency

  • Execute responsibilities with a high degree of autonomy and limited oversight, independently managing programs, refining processes, and engaging stakeholders

Required qualifications, capabilities and skills
  • Bachelor’s degree in a quantitative field such as Computer Science, Operations Research, Mathematics, Engineering, Econometrics, Statistics, or related discipline with 3+ years of relevant experience, or an advanced degree with 2+ years of experience

  • Exceptional interpersonal and collaboration skills with the ability to explain complex mathematical concepts in accessible terms and influence business partners at all levels

  • Proven track record of delivering analytics and insights to multiple levels of management, from operational teams to senior executives

  • Hands‑on experience with data mining techniques, analytical methodologies, and translating analysis into business strategy implementation

  • Proficiency in data analysis programming languages such as Python or SAS, with experience in Big Data technologies including Snowflake, Databricks, or equivalent platforms

  • Strong SQL skills and demonstrated experience working with relational databases to extract, manipulate, and analyze data

  • Experience with data visualization techniques and reporting tools such as Tableau, Alteryx, or comparable platforms to create compelling visual narratives

  • Advanced analytical, interpretive, and problem‑solving skills with the ability to tackle ambiguous business challenges and derive actionable solutions

  • Excellent written and oral communication skills, with the ability to distill complex analytical findings into clear, concise insights for senior business leaders and non‑technical audiences

Preferred qualifications, capabilities and skills
  • Experience developing executive‑ready dashboards and performance measurement frameworks for marketing and portfolio analytics

  • Demonstrated ability to influence prioritization and decisions through structured analytics storytelling and clear business recommendations

  • Experience working with cross‑functional partners in marketing, product, finance, and risk to deliver measurable business outcomes

  • Experience identifying and scaling process improvements that enhance data quality, repeatability, and reporting efficiency

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