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Statistical Analyst Jobs in Dallas, TX (NOW HIRING)

SoFi

Fraud Model Analyst

Frisco, TX · On-site

The ideal candidate has a strong analytical and statistical mindset, is comfortable working with complex datasets using SQL and Python, understands predictive model performance, and can translate ...

Orionyx Enginnering

Data Analyst

Dallas, TX · Remote

$23.50 - $30.50/hr

Utilize statistical methods and analytical techniques to interpret complex data sets related to engineering projects, performance metrics, and operational efficiency. * Identify trends, patterns, and ...

Cetera

Investment Research Analyst

Dallas, TX · Hybrid

Experience with financial modeling, data visualization, and statistical analysis. Familiarity with investment concepts, portfolio theory, and asset allocation. Excellent communication skills and ...

Office Depot

Compensation Analyst

Grand Prairie, TX

Perform statistical analysis and prepare reporting on compensation trends and program performance. * Participate in market surveys and contribute to salary benchmarking initiatives. * Assist with ...

Cetera

Investment Research Analyst

Dallas, TX · Hybrid

Experience with financial modeling, data visualization, and statistical analysis. Familiarity with investment concepts, portfolio theory, and asset allocation. Excellent communication skills and ...

Office Depot

Compensation Analyst

Grand Prairie, TX · On-site

$80K/yr

Perform statistical analysis and prepare reporting on compensation trends and program performance. * Participate in market surveys and contribute to salary benchmarking initiatives. * Assist with ...

T-Mobile

Analyst, Credit Risk Mgmt - Strategy

Frisco, TX · On-site

$83K - $151K/yr

Utilize statistical segmentation techniques to identify new opportunities * Extract, load and transform data from multiple sources necessary for statistical, reporting and ad-hoc analysis * Perform ...

T-Mobile

Sr Analyst, Credit Risk Mgmt

Frisco, TX · On-site

$84K - $152K/yr

Apply statistical segmentation techniques to identify new opportunities * Perform sophisticated qualitative and quantitative analysis of credit polices to ensure financial goals are being attained

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Statistical Analyst information

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$27.6K

$64.8K

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How much do statistical analyst jobs pay per year?

As of Sep 7, 2026, the average yearly pay for statistical analyst in Dallas, TX is $64,826.00, according to ZipRecruiter salary data. Most workers in this role earn between $53,800.00 and $74,500.00 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.
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The top searched job categories for Statistical Analyst jobs in Dallas, TX are:

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Cities near Dallas, TX with the most Statistical Analyst job openings:

Statistical Analyst jobs near you
Infographic showing various Statistical Analyst job openings in Dallas, TX as of August 2026, with employment types broken down into 88% Full Time, 7% Part Time, and 5% Contract. Highlights an 84% Physical, 6% Hybrid, and 10% Remote job distribution, with an average salary of $64,826 per year, or $31.2 per hour.

Fraud Model Analyst

SoFi

Frisco, TX • On-site

Full-time

Re-posted 2 days ago

Job description

Employee Applicant Privacy Notice
Who we are:
Shape a brighter financial future with us.
Together with our members, we're changing the way people think about and interact with personal finance.
We're a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we're at the forefront. We're proud to come to work every day knowing that what we do has a direct impact on people's lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world.
The role:
We are looking for a Fraud Model Analyst to join our Fraud Model Development team, with a focus on governance, oversight, and lifecycle management of third-party (vendor) fraud models. This role will be responsible for ensuring vendor models are compliant, well-documented, and effectively monitored within SoFi's fraud ecosystem.
This role will partner closely with Fraud Model Development, Fraud Strategy, Product, Operations, and Engineering to establish consistent analytical frameworks for measuring fraud performance, evaluating model and strategy changes, and identifying opportunities to improve fraud detection while minimizing false positives and member friction.
The individual will use large-scale fraud, transaction, and member data to evaluate model and strategy performance, conduct statistical and diagnostic analyses, design and analyze experiments, and develop scalable monitoring and measurement frameworks. The role will also contribute to fraud model development initiatives through feature analysis, performance benchmarking, threshold analysis, and production model evaluation.
The ideal candidate has a strong analytical and statistical mindset, is comfortable working with complex datasets using SQL and Python, understands predictive model performance, and can translate analytical findings into clear recommendations for technical and business stakeholders.
What you'll do:
The Fraud Model Analyst will help SoFi scale and govern vendor fraud models by:
Managing the end-to-end lifecycle of vendor fraud models, including onboarding, documentation, monitoring, and periodic reviewsPartnering with Model Risk Management (MRM), Legal, and Compliance teams to ensure adherence to governance and regulatory requirementsCoordinating with external vendors to obtain model documentation, technical details, and performance insightsAnalyzing model performance metrics (e.g., fraud capture, false positive rates, drift) and identifying risks or improvement opportunitiesInvestigating model behavior and data issues using SQL and internal datasets to support root cause analysisSupporting fraud model development initiatives by contributing to feature analysis, performance benchmarking, and strategy designCollaborating with Fraud Strategy, Data Science, and Engineering teams to integrate vendor models into fraud decisioning frameworksPreparing and maintaining model documentation, validation materials, and audit responsesSupporting ongoing monitoring and reporting of vendor model performance, including identifying degradation and recommending actionsActing as a bridge between Data Science, Engineering, Fraud Strategy, and Risk/Compliance teams to ensure alignmentManaging multiple models and timelines, ensuring timely delivery of governance and reporting requirements
What you'll need:
  • 3+ years of experience in data science, fraud analytics, risk analytics, model analytics, or another related quantitative role.
  • Bachelor's degree in a quantitative field such as Statistics, Mathematics, Economics, Engineering, Computer Science, Data Science, or equivalent experience.
  • Strong analytical and statistical skills with experience evaluating predictive model performance and identifying underlying drivers of performance changes.
  • Proficiency in SQL and Python for data analysis, statistical analysis, model evaluation, and investigation.
  • Experience working with fraud or predictive model performance metrics such as fraud capture rate, false-positive rate, precision/recall, AUC, drift, and other model and business performance measures.
  • Familiarity with data science and machine-learning workflows and the ability to work with datasets to support model analysis, benchmarking, monitoring, and validation.
  • Understanding of experimental design and statistical significance, with experience analyzing A/B tests, control/treatment groups, champion/challenger tests, backtests, or similar experiments.
  • Experience performing root-cause analysis, segmentation, cohort analysis, or other diagnostic analyses to identify drivers of performance changes.
  • Ability to evaluate model thresholds and understand trade-offs between fraud detection, false positives, member friction, operational impact, and business outcomes.
  • Experience working with large-scale transaction, member, fraud, or operational datasets.
  • Experience developing analytical reporting, dashboards, or monitoring frameworks using Tableau, Looker, Power BI, or similar tools.
  • Strong communication and data storytelling skills with the ability to translate technical and statistical concepts into clear business recommendations.
  • Experience working with cross-functional stakeholders across Data Science, Fraud Strategy, Product, Engineering, Operations, or Risk.
  • Strong organizational skills and the ability to manage multiple analytical initiatives and priorities in a fast-moving environment
Nice to have:
  • Experience working directly with fraud models or contributing to fraud model development.
  • Experience in payments fraud, account takeover, first-party fraud, transaction fraud, identity fraud, or financial crime analytics.
  • Familiarity with machine-learning concepts and common classification methodologies, with the ability to interpret model outputs, performance metrics, and trade-offs.
  • Experience with model monitoring, model drift analysis, backtesting, threshold optimization, segmentation, feature analysis, or champion/challenger frameworks.
  • Experience measuring the production impact and incremental value of machine-learning models.
  • Understanding of common fraud modeling and measurement challenges, including label maturity, delayed outcomes, class imbalance, changing fraud patterns, data leakage, and selection bias.
  • Experience with automated analytical workflows or reusable Python/SQL frameworks for model and fraud performance analysis.
  • Familiarity with Model Risk Management (MRM), model governance, documentation, and monitoring requirements.
  • Experience working with third-party/vendor fraud models and evaluating their performance alongside internally developed models.
  • Exposure to regulatory and compliance environments within financial services.

Compensation and Benefits
The base pay range for this role is listed below. Final base pay offer will be determined based on individual factors such as the candidate's experience, skills, and location.
To view all of our comprehensive and competitive benefits, visit our Benefits at SoFi page!
SoFi provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion (including religious dress and grooming practices), sex (including pregnancy, childbirth and related medical conditions, breastfeeding, and conditions related to breastfeeding), gender, gender identity, gender expression, national origin, ancestry, age (40 or over), physical or medical disability, medical condition, marital status, registered domestic partner status, sexual orientation, genetic information, military and/or veteran status, or any other basis prohibited by applicable state or federal law.
The Company hires the best qualified candidate for the job, without regard to protected characteristics.
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
New York applicants: Notice of Employee Rights
SoFi is committed to an inclusive culture. As part of this commitment, SoFi offers reasonable accommodations to candidates with physical or mental disabilities. If you need accommodations to participate in the job application or interview process, please let your recruiter know or email accommodations@sofi.com.
We are unable to accommodate remote work from Hawaii, Alaska or Puerto Rico at this time.
Internal Employees
If you are a current employee, do not apply here - please navigate to our Internal Job Board in Greenhouse to apply to our open roles.

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