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Statistical Modeling Analyst 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.

WI · On-site

$110 - $150/hr

Apply statistical and machine‐learning techniques to large, complex datasets for feature ... analysis, and value-at-risk* Knowledgeable of modeling systems and/or computer programming ...

Conduct statistical analysis, scenario analysis, sensitivity testing, and forecasting exercises to assess market risks and opportunities. * Evaluate model performance through validation, back-testing ...

Conduct statistical analysis, scenario analysis, sensitivity testing, and forecasting exercises to assess market risks and opportunities. * Evaluate model performance through validation, back-testing ...

Senior Credit Risk Modeling Analyst will have the ability to work a hybrid schedule (remote/onsite ... Apply statistical and machinelearning techniques to large, complex datasets for feature engineering ...

Senior Credit Risk Modeling Analyst will have the ability to work a hybrid schedule (remote/onsite ... Apply statistical and machinelearning techniques to large, complex datasets for feature engineering ...

WI · On-site

$100 - $150/hr

Senior Credit Risk Modeling Analyst will have the ability to work a hybrid schedule (remote/onsite ... Apply statistical and machine‑learning techniques to large, complex datasets for feature ...

Conduct statistical analysis, scenario analysis, sensitivity testing, and forecasting exercises to assess market risks and opportunities. * Evaluate model performance through validation, back-testing ...

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Statistical Modeling Analyst information

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How much do statistical modeling analyst jobs pay per year?

As of Aug 24, 2026, the average yearly pay for statistical modeling analyst in the United States is $70,450.00, according to ZipRecruiter salary data. Most workers in this role earn between $58,500.00 and $81,000.00 per year, depending on experience, location, and employer.

What is a statistical modeling analyst?

A Statistical Modeling Analyst uses mathematical and statistical techniques to analyze data and create predictive models that help organizations make informed decisions. They work with large datasets, identify patterns, and develop models to forecast trends or optimize business processes. This role often requires expertise in programming languages like Python, R, or SQL and proficiency in machine learning techniques. Analysts collaborate with cross-functional teams to translate data insights into actionable strategies. Industries such as finance, healthcare, marketing, and technology rely heavily on their expertise to drive data-driven decision-making.

What are the key skills and qualifications needed to thrive as a statistical modeling analyst?

To thrive as a Statistical Modeling Analyst, you need a solid foundation in mathematics, statistics, and data analysis, typically supported by a degree in a quantitative field such as statistics, mathematics, or economics. Proficiency in statistical software tools like SAS, R, Python, and data visualization platforms is highly valued, along with relevant certifications such as SAS Certified Specialist or similar. Strong analytical thinking, attention to detail, and effective communication skills are important soft skills for translating complex data into actionable insights. These abilities allow Statistical Modeling Analysts to provide accurate analyses, facilitate better business decisions, and collaborate effectively with cross-functional teams.

What types of projects or team collaborations can a statistical modeling analyst expect?

As a Statistical Modeling Analyst, you will often work on projects such as developing predictive models, analyzing large datasets, and creating reports to guide business strategies. Collaboration is common, as you'll frequently partner with data engineers, business analysts, and stakeholders from departments like marketing or finance to define modeling objectives and interpret results. You may be involved in regular meetings to discuss data trends, troubleshoot issues, and present your findings to both technical and non-technical audiences. This dynamic, team-oriented environment fosters learning, exposure to diverse business problems, and opportunities for career growth as your expertise increases.

What does a statistical modeling analyst do?

A statistical modeling analyst develops and applies statistical models to analyze data, identify patterns, and support decision-making. They use tools like R, Python, or SAS and often work with large datasets to create predictive models, requiring strong analytical skills and knowledge of statistical methods.
More about Statistical Modeling Analyst jobs

What states have the most Statistical Modeling Analyst jobs?

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

Infographic showing various Statistical Modeling Analyst job openings in the United States as of August 2026, with employment types broken down into 86% Full Time, 11% Part Time, and 3% Contract. Highlights an 82% Physical, 5% Hybrid, and 13% Remote job distribution, with an average salary of $70,450 per year, or $33.9 per hour.

Sr Statistical Modeling Analyst

BECU

Remote

$99K - $186K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 4 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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