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Statistical Modeling Jobs (NOW HIRING)

The Sr Statistical Modeling Analyst will manage statistical model development and implementation independently and through collaboration with stakeholders throughout the credit union.

Sr Statistical Modeling Analyst

OR · On-site +1

$99K - $186K/yr

The Sr Statistical Modeling Analyst will manage statistical model development and implementation independently and through collaboration with stakeholders throughout the credit union.

Statistical Modeler

San Antonio, TX · On-site

$49.50 - $64/hr

Knowledge on Statistics and Modeling is preferred. Strong understanding of structure and knowledge of Banking and Insurance Industry Product knowledge Ability to analyze issues, identify trends and ...

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Statistical Modeling information

See salary details

$36.5K

$55.4K

$99K

How much do statistical modeling jobs pay per year?

As of Sep 3, 2026, the average yearly pay for statistical modeling in the United States is $55,350.00, according to ZipRecruiter salary data. Most workers in this role earn between $42,000.00 and $60,000.00 per year, depending on experience, location, and employer.

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 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 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 do statistical modeling do?

Statistical modeling involves developing mathematical representations of data to analyze and predict patterns or outcomes. Professionals in this field use tools like statistical software and techniques such as regression or hypothesis testing to interpret data and support decision-making across various industries.
More about Statistical Modeling jobs

What cities are hiring for Statistical Modeling jobs?

Cities with the most Statistical Modeling job openings:

What states have the most Statistical Modeling jobs?

States with the most job openings for Statistical Modeling jobs include:

Infographic showing various Statistical Modeling job openings in the United States as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $55,350 per year, or $26.6 per hour.

Sr Statistical Modeling Analyst

BECU

Remote

$99K - $186K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 15 days ago


BECU rating

8.7

Company rating: 8.7 out of 10

Based on 24 frontline employees who took The Breakroom Quiz


Job description

Is it surprising to hear that a financial institution of 1.5 million members and over $30 billion in managed assets say that success comes from focusing on people, not profits?
Our "people helping people" philosophy has guided us since 1935, driving our deep commitment to serving our members, communities, and each other. When you join our team, you become part of a purpose-driven organization where your work makes a real difference.
While we're proud of our history, we're even more excited about our future. With business and technology transformation on the horizon, there's never been a better time to be part of BECU.


You bring more than your expertise to your role, and that matters here. Your story, perspectives, and lived experiences help shape belonging at BECU and deepen how we connect with and support our employees, our members, and our communities.


PAY RANGE

The Target Pay Range for this position is $128,900.00-$157,500.00 annually. The full Pay Range is $99,900.00 - $186,400.00 annually. At BECU, compensation decisions are determined using factors such as relevant job-related skills, experience, and education or training. Should an offer for employment be made, we will consider individual qualifications. In addition to your salary, compensation incentives are available for the hired applicant. Incentives are performance based and targets vary by role.

BENEFITS - because people helping peoplestarts with supporting you

  • 401(k) Company Match (up to 3%)

  • 4% annual contribution to your 401(k) by BECU

  • Medical, Dental and Vision (family contributions as well)

  • PTO Program + Exchange Program

  • Tuition Reimbursement Program

  • BECU Cares volunteer time off + donation match

SUMMARY

The Sr Statistical Modeling Analyst is responsible for the development and management of statistically derived credit risk modeling used by the credit union for loan or deposit originations, account management, collections, loan loss forecasting, capital plans and stress testing. The Sr Statistical Modeling Analyst will manage statistical model development and implementation independently and through collaboration with stakeholders throughout the credit union.

RESPONSIBILITIES

  • Develop, re-develop, and calibrate statistical models using statistical analytical packages; including but not limited to: Probability of Default (PD), Loss Given Default (LGD), and Exposure at Default (EAD) models for credit decision scorecard, loss forecasting, reserving, and economic capital use cases. Support documentation and execution of statistical models under the direction of senior level peers and leadership.
  • Research and apply enhancements to existing suite of models to improve accuracy, partnering with senior level peers and leadership. Research statistical methods and apply enhancements to existing suite of models to improve accuracy. Scope includes Probability of Default (PD), Loss Given Default (LGD), Exposure at Default (EAD), and loan loss forecast models.
  • Collaborate with business partners and product management to help interpret model results and assess the appropriateness of statistical methods and models for addressing business questions and generating actionable insights. Provide value-added solutions for the enhancement of risk-return trade-off through the application of advanced analytical packages.
  • Participate in annual model reviews and performance testing.
  • Manage the data request and systems testing process. Gather and evaluate data for reliability and usability and research and apply data treatment methods.
  • Work with senior members of the team on all aspects of the advanced credit risk models development life cycle.
  • Participate in team meetings related to statistical model development.
  • Deliver regular reports of modeling results to include impacts of originations, servicing, collection, loss mitigation and asset liquidation strategies and performance.
  • Maintain a thorough knowledge relating to loan portfolio trends and composition, while analyzing and presenting model outputs.
  • Utilize data warehouse information, along with model results, to assist in the development of credit risk management credit risk strategies.
  • Identify opportunities for efficiency and effectiveness, including reporting requirements.
  • Develop and maintain statistical modeling documentation and change control documentation.
  • Perform other duties as assigned.

QUALIFICATIONS

  • Master's degree or foreign equivalent in a quantitative discipline such as statistics, math, finance, or economics required. Coursework in statistics at either the bachelor's, master's or PhD level required.
  • Minimum 3 years of functional experience in statistical modeling required including credit risk modeling experience in one or more of the following product areas: real estate secured loan products (mortgage, home equity), auto, credit card or commercial loan products.
  • Sound knowledge of statistical modeling concepts, including logistic regression, survival analysis, Markov chain analysis and time series methodologies, with experience developing and validating Probability of Default (PD), Exposure at Default (EAD), and Loss Given Default (LGD) models required.
  • Knowledge of artificial intelligence (AI) and machine learning (ML) tools required.
  • Knowledge of three or more of the following statistical analytical packages required: SAS, Python, SQL and R.
  • Experience with statistical modeling for capital planning and stress testing preferred.
  • Experience with Comprehensive Capital Analysis Review (CCAR), Dodd-Frank Act Stress Testing (DFAST) and Basel Regulatory Capital Framework preferred.
  • Experience with modelling techniques including logistic regression, multivariate analysis, and Monte Carlo preferred.
  • Excellent analytical and problem-solving skills required.
  • Experience in verbal and written communication of complex statistical insights and implications to Credit Union strategy and value creation preferred.
  • Ability to interact with management officials at all levels, as well as other risk and model management personnel throughout the Credit Union required.
  • Ability to analyze and reconcile large volume of data so that it can be summarized and eventually used for management decisions required.
EEO Statement:


BECU is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, veteran status, disability, sexual orientation, gender identity, or any other protected status.


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