Data Analyst

Company Information

PACCAR is a Fortune 500 company established in 1905. PACCAR Inc is recognized as a global leader in the commercial vehicle, financial, and customer service fields with internationally recognized brands such as Kenworth, Peterbilt, and DAF trucks. PACCAR is a global technology leader in the design, manufacture and customer support of high-quality light-, medium- and heavy-duty trucks under the Kenworth, Peterbilt and DAF nameplates.

PACCAR designs and manufactures advanced diesel engines and also provides customized financial services, information technology and truck parts related to its principal business.

This position is located at PACCAR's global headquarters in downtown Bellevue, Washington, and provides an exciting opportunity to support the strategic direction of PACCAR by developing and applying analytical models that identify and quantify risk in PACCAR's global portfolio of financial products.

As a Data Analyst within the Portfolio Risk and Analysis Group, you will provide analytically sound risk models that inform credit decisions by PACCAR's finance organizations in Europe, North America, Latin America, and Australia, as well as senior management and company executives. You will utilize your education and work experience to drive new projects and improvements to existing processes. Company executives and analytic partners will rely on you for timely, trustworthy, and relevant business insights gained through best practices in data science and advanced analytic techniques.

Success in this role will hinge on your curiosity, ability to work well in ambiguity, a passion for learning, and adept communication skills.

• Manage and document the full lifecycle of analytic projects from problem statement through solution performance monitoring.
• Provide accurate, relevant, and meaningful analysis to management to support strategic and tactical decision-making.
• Employ appropriate AI/ML algorithms in creation and deployment of models that support initiatives for risk analysis and automated credit decisioning.
• Develop and evaluate predictive models of credit risk and portfolio performance.
• Collaborate with PACCAR's global credit divisions to develop consistent credit scorecards and risk models.
• Access database and source system to extract required data for analysis.
• Acquire, clean, validate, and explain the data used for analytic model development, including variance reporting, sensitivity analysis, and outlier/anomaly detection.
• Develop and implement process improvements to enhance data analysis and modeling capabilities, increasing the speed, accuracy, and efficiency of our work.
• Conduct 'quick-turn' analysis to support emerging business decision‑making requirements.
• Effectively communicate analytic results that demonstrate business impacts to senior managers and executives.
• Collaborate with entire Portfolio Risk and Analysis Team to introduce new approaches and perspectives across all team functions.

Qualifications & Skills

• Bachelor's degree in Analytics, Statistics, Business, Finance, Computer Science or related field.
• 3+ years of applicable job experience.
• Strong foundation in statistics and ML (e.g., logistic/stepwise regression, chi-squared tests, ROC/AUC).
• Experience building and evaluating predictive models in risk, credit, or similar domains.
• Advanced SQL skills and experience with cloud data warehouses (preferably Snowflake).
• Proficiency in R and/or Python for data analysis and modeling.
• Strong data skills: acquisition, cleaning, validation, outlier/anomaly detection, variance/sensitivity analysis.
• Experience managing the full analytics lifecycle from problem definition through model deployment and monitoring.
• Ability to clearly communicate complex analytical results to non-technical and executive audiences.
• Solid business acumen and demonstrated problem-solving ability.
• Ability to perform quick-turn analyses under tight timelines.
• Self-directed, highly motivated, with strong attention to detail.
• Collaborative mindset and ability to work effectively with global, cross-functional stakeholders.

Preferred Experience/ Skills/Competencies

• MBA or Master's degree in Computational Finance, Analytics, MIS or related field.
• Professional certifications such as CFA, CBIP, or MSCE in Business Intelligence.
• Experience with the AWS suite, specifically Amazon S3, AWS Lambda, and Apache Airflow.
• Experience in credit risk modeling, scorecards, or financial services (lending, leasing, or related areas).
• Familiarity with model governance/model risk management and regulatory expectations.
• Experience deploying models to production and supporting model monitoring.
• Experience with additional ML methods (e.g., gradient boosting, random forests, XGBoost/LightGBM).
• Experience creating dashboards and reports in Tableau or similar BI tools.
• Experience with Snowflake-specific features and performance optimization.
• Experience with version control (Git) and collaborative…