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Statistical Analyst Jobs in Delaware (NOW HIRING)

Bachelor's Degree required in statistics, mathematics, physics, economics, or other analytical or quantitative discipline. Master's Degree or PhD preferred. 3+ years in data science, machine learning ...

New

The Senior Pricing Analyst is responsible for conducting complex data analyses and developing ... Apply statistical modeling methods to determine the potential impact of pricing strategies on ...

Bachelor's degree in health informatics, Data Science, Statistics, Public Health or a related field. * Minimum of 2-3 of Data Analysis experience in a healthcare environment Language Skills:

... statistical modeling, Advise clients & internal teams on the right analytics algorithm, platforms and approaches to take in addressing complex, open-ended business problems. Position: 2 Job Title:

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Statistical Analyst information

See Delaware salary details

$30K

$70.5K

$117.6K

How much do statistical analyst jobs pay per year?

As of Sep 7, 2026, the average yearly pay for statistical analyst in Delaware is $70,511.00, according to ZipRecruiter salary data. Most workers in this role earn between $58,600.00 and $81,100.00 per year, depending on experience, location, and employer.

What is a statistical analyst?

A statistical analyst reviews data and uses models to develop practical solutions to problems. As a statistical analyst, your primary duties involve planning analyses, reviewing collected data, designing statistical models, using statistical analysis software programs, and reporting your findings to your superiors. This job requires a bachelor’s degree in mathematics, computer science, or a related field. Additional qualifications include work experience in an office environment, familiarity with relevant industry computer software, and strong creative thinking abilities. You also need excellent analytical, mathematical, and research skills. You can find statistical analyst positions in a wide variety of industries.

What does a statistical analyst do?

A Statistical Analyst is responsible for collecting, analyzing, and interpreting data to help organizations make informed decisions. They use statistical methods and software to identify trends, patterns, and relationships within large datasets. Their work supports areas such as business strategy, scientific research, healthcare, and government policy. Statistical Analysts often present their findings through reports, visualizations, and presentations to stakeholders. Their insights are crucial for evidence-based planning and problem-solving.

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

To thrive as a Statistical Analyst, you need a strong background in statistics, mathematics, and data analysis, usually supported by a relevant degree such as statistics, mathematics, or economics. Proficiency with statistical software such as R, SAS, SPSS, or Python, as well as experience with data visualization tools, is typically required. Attention to detail, problem-solving skills, and the ability to communicate complex findings clearly are valuable soft skills in this role. These capabilities are crucial for transforming data into actionable insights that support informed decision-making in organizations.

What are some common challenges statistical analysts face when interpreting large datasets, and how can they overcome them?

Statistical Analysts often encounter challenges such as dealing with missing or inconsistent data, managing data from multiple sources, and ensuring that their analyses are not biased by outliers or erroneous entries. To overcome these issues, analysts use data cleaning techniques, robust validation processes, and statistical methods to account for anomalies. Collaborating closely with data engineers and subject matter experts also helps ensure that the data is accurate and relevant, leading to more reliable insights.

What is the difference between Statistical Analyst vs Data Scientist?

AspectStatistical AnalystData Scientist
Required CredentialsBachelor's degree in statistics, mathematics, or related fieldBachelor's or higher in computer science, statistics, or related field; often includes advanced degrees
Work EnvironmentCorporate, finance, healthcare, or government settings focusing on data analysisTech companies, research, and industries requiring complex data modeling
Employer & Industry UsageCommon in finance, healthcare, and marketing sectorsPrevalent in technology, e-commerce, and research sectors

While both roles analyze data, Statistical Analysts primarily focus on interpreting data using statistical methods, often with less emphasis on programming. Data Scientists typically handle larger datasets, develop predictive models, and utilize advanced programming skills. The roles overlap in data analysis but differ in complexity and scope.

Do statistical analysts make a lot of money?

Statistical analysts typically earn competitive salaries that vary by experience, education, and industry. According to industry data, the median annual wage for statistical analysts is above the national average, with higher earnings possible for those with advanced skills in data analysis tools like R or Python and relevant certifications. Salary potential increases with experience and specialization in fields such as finance, healthcare, or technology.

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

The most popular types of Statistical Analyst jobs in Delaware are:

What are popular job titles related to Statistical Analyst jobs in Delaware?

For Statistical Analyst jobs in Delaware, the most frequently searched job titles are:

What job categories do people searching Statistical Analyst jobs in Delaware look for?

The top searched job categories for Statistical Analyst jobs in Delaware are:

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

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

Infographic showing various Statistical Analyst job openings in Delaware as of August 2026, with employment types broken down into 88% Full Time, 8% Part Time, and 4% Contract. Highlights an 79% Physical, 8% Hybrid, and 13% Remote job distribution, with an average salary of $70,511 per year, or $33.9 per hour.

Specialized Analytics Senior Analyst

Citi

New Castle, DE

$83K - $105K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 3 days ago

New


Citibank rating

8.4

Company rating: 8.4 out of 10

Based on 179 frontline employees who took The Breakroom Quiz

39th of 175 rated banks


Job description

Job Description As part of Citi's Financial Crimes and Fraud Prevention - Modeling and Data organization, this role leverages advanced machine learning tools and data mining techniques to identify and combat fraud. A key focus of the role is on data and feature engineering; transforming raw and complex datasets into optimized inputs for developing high-performance fraud models. The role will be responsible for developing and implementing sophisticated fraud models aimed at preventing and mitigating fraud risks across the full fraud lifecycle including application fraud, synthetic ID fraud, account takeover, and evolving fraud attack methods.

The ideal candidate will bring a strong technical background in data processing, feature engineering, and data manipulation, playing a pivotal role in enabling the development of effective and scalable fraud models. The role requires expertise in extracting and engineering key features from large datasets, ensuring that models are not only accurate but also resilient against emerging fraud patterns. The role will work closely with technology teams, fraud analytics, and various business partners to stay informed about business and technology shifts, identifying both potential and existing fraud impacts.

Technical proficiency in model optimization, algorithm development, and real-time analytics is essential for enhancing fraud prevention efforts. Responsibilities Lead data and feature engineering efforts to extract, transform, and prepare high-quality data inputs for fraud model development, focusing on identifying key attributes that drive accurate fraud detection. Build predictive models and machine-learning and AI algorithms with large amounts of structured and unstructured data.

Ownership and management of fraud models, risk appetite execution and defect analysis. Design, develop, and implement advanced machine learning models to detect and prevent fraud across the entire lifecycle, including application fraud, synthetic ID fraud, account takeover, and evolving attack schemes. Utilize advanced data processing techniques to manage large, complex datasets, including data cleaning, normalization, and augmentation, ensuring robust model performance.

Conduct comprehensive exploratory data analysis (EDA) to uncover hidden patterns, trends, and anomalies that can inform model development and feature engineering. Collaborate closely with technology teams, fraud analytics, and business partners to align on data strategies, stay updated on industry trends, and proactively identify potential and existing fraud risks. Continuously optimize and refine fraud models through feature selection, hyperparameter tuning, and ongoing performance monitoring, ensuring models remain adaptive to new fraud tactics.

Support model deployment and integration into production systems, ensuring seamless real-time fraud detection and efficient feedback loops for continuous model improvement. Evaluate and select appropriate machine learning algorithms and tools based on specific fraud detection needs and data characteristics. Engage in cross-functional initiatives to enhance data quality and governance, improving overall fraud prevention capabilities.

Participate in model validation and testing processes to ensure compliance with regulatory standards and alignment with best practices in fraud risk management. Generate and manage regular and ad-hoc reporting to enable effective monitoring and identification of emerging trends. Qualifications: Bachelor's Degree required in statistics, mathematics, physics, economics, or other analytical or quantitative discipline.

Master's Degree or PhD preferred. 3+ years in data science, machine learning, or advanced analytics. Strong Technical Skills: Proficiency in programming languages such as Python, R, or SQL for data manipulation, feature engineering, and model development.

Strong experience with data processing tools and libraries (e.g., Pandas, Numpy, PySpark) for handling large and complex datasets. Deep understanding of machine learning algorithms (e.g., decision trees, gradient boosting, neural networks, natural language processing) and statistical modeling techniques used for fraud detection Expertise in feature engineering, including creating, selecting, and refining features to improve model accuracy and performance. Data Engineering: Experience with building and optimizing data pipelines, ETL professes, and real-time data streaming for fraud detection solutions

Machine Learning Operations: Familiarity with model development, monitoring, and versioning in production environments. Analytics Skills: Strong ability to conduct exploratory data analysis (EDA) and identify actionable insights from large datasets to drive model development. Collaboration: Proven track record of working cross-functionally with technology, analytics, and business teams to implement and optimize fraud prevention strategies.

Communication: Ability to translate complex technical findings into clear, actionable insights for non-technical stakeholders and business leaders. Problem-Solving: Strong problem-solving skills with the ability to think critically and creatively in a fast-paced environment. Regulatory Compliance: Familiarity with regulatory requirements and best practices related to fraud modeling and risk management.

Multi-Tasking and Deadline Management: Demonstrated ability to manage multiple projects and priorities simultaneously while meeting tight deadlines. Attention to Detail: High level of attention to detail and precision in data analysis, model development, and reporting. Intellectual Curiosity: Strong intellectual curiosity and eagerness to stay updated with the latest developments in data science, machine learning, and fraud detection techniques.

609912 ------------------------------------------------------ Job Family Group: Decision Management ------------------------------------------------------ Job Family: Specialized Analytics (Data Science/Computational Statistics) ------------------------------------------------------ Time Type: Full time ------------------------------------------------------ Primary Location: San Antonio Texas United States ------------------------------------------------------ Primary Location Full Time Salary Range: $96,960.00 - $145,440.00 In addition to salary, Citi's offerings may also include, for eligible employees, discretionary and formulaic incentive and retention awards. Citi offers competitive employee benefits, including: medical, dental & vision coverage; 401(k); life, accident, and disability insurance; and wellness programs. Citi also offers paid time off packages, including planned time off (vacation), unplanned time off (sick leave), and paid holidays

For additional information regarding Citi employee benefits, please visit citibenefits.com. Available offerings may vary by jurisdiction, job level, and date of hire. ------------------------------------------------------ Most Relevant Skills Please see the requirements listed above

------------------------------------------------------ Other Relevant Skills For complementary skills, please see above and/or contact the recruiter. ------------------------------------------------------ Anticipated Posting Close Date: Sep 10, 2026 ------------------------------------------------------ Automated Processing and AI We use automated processing, including artificial intelligence, for our legitimate business interests (or our reasonable and appropriate business purposes) to identify and align the candidate's skills and abilities with a specific job opening. Additionally, if you so choose, or consent, we can match your skills and abilities to other suitable roles at Citi.

Importantly, all our hiring processes and decisions, including determining your suitability for a role, are conducted, checked, and decided by individuals. Our automated processing and AI do not involve relying on automatic or autonomous decision-making. Please refer to any Jurisdictional Considerations, with specific provisions for your country (where relevant) for further details.

Illinois residents - AI Notice and Right ------------------------------------------------------ Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law. If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity review Accessibility at Citi. View Citi's EEO Policy Statement and the Know Your Rights poster.


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About Citigroup Inc

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We live in an increasingly complex world. Companies these days are either born global or are going global at record speed. Business and geopolitics are forging an entirely new dynamic and consumers now expect financial services to be a seamless part of their digital lives. Citi is a bank that’s uniquely positioned for this moment. Through our vast global network and our on-the-ground expertise, we can connect the dots, anticipate change and empathize the needs of our clients and customers in ways that other banks simply cannot. Citi's mission is to serve as a trusted partner to our clients by responsibly providing financial services that enable growth and economic progress. We have set expectations for how we must act to bring our mission to life. These expectations are at the heart of our Leadership Principles – we take ownership, we deliver with pride and we succeed together.

Industry

Banking and credit intermediation

Company size

5,001 - 10,000 Employees

Headquarters location

New York City, NY, US