Statistical Modeler

OneMagnify•Dearborn, MI

19h

About The Position

OneMagnify is a global performance marketing organization working at the intersection of brand marketing, technology, and analytics. The Company’s core offerings accelerate business, amplify real-time results, and help set their clients apart from their competitors. OneMagnify partners with clients to design, implement and manage marketing and brand strategies using analytical and predictive data models that provide valuable customer insights to drive higher levels of sales conversion. OneMagnify’s commitment to employee growth and development extends far beyond typical approaches. We take great pride in fostering an environment where each of our 700+ colleagues can thrive and achieve their personal best. OneMagnify has been recognized as a Top Workplace, Best Workplace and Cool Workplace in the United States for 10 consecutive years and recently was recognized as a Top Workplace in India. We are seeking an experienced Senior Statistical Modeler to design, develop, validate, and deploy predictive models across financial, credit, and customer analytics domains. This role requires deep statistical expertise, strong programming capability across SAS, Python, and SQL, and experience working with large-scale financial or behavioral datasets. About You: You have a strong foundation in statistical modeling and quantitative analysis. You are comfortable working across SAS, Python, and SQL in production environments. You have hands-on experience building predictive or risk models in a professional setting. You are detail-oriented and prioritize documentation. You can translate complex statistical outputs into actionable business recommendations. You are motivated to operate in a fast-paced, client-facing environment where rigor and execution matter.

Requirements

Graduate degree or equivalent experience in Statistics, Mathematics, Econometrics, Operations Research, Data Science, or a related field
4+ years of hands-on experience building and validating predictive models in a professional environment
Demonstrated experience crafting statistical analysis and communicating results to business stakeholders
Proficiency in exploratory data analysis, feature engineering, logistic regression, and other advanced statistical techniques
Experience and proficiency working with SAS, SQL, and Python
Strong oral and written communication skills

Nice To Haves

Preferably, experience and solid comprehension of Finance, Insurance, or Credit Risk Analysis

Responsibilities

Collaborate with cross-functional teams to develop, validate, and deploy predictive models related to: Credit risk and default propensity Fraud detection and anomaly identification Customer lifetime value and attrition Propensity and segmentation modeling
Apply advanced statistical and machine learning techniques including: Logistic regression and generalized linear models Decision trees, random forest, and gradient boosting
Conduct exploratory data analysis, feature engineering, and dataset preparation using SQL, Python, and SAS.
Extract and transform large datasets from enterprise data environments.
Monitor model performance and recommend recalibration based on drift or business changes.
Support production deployment and automated scoring processes.
Prepare technical documentation, model summaries, and stakeholder presentations.
Collaborate with cross-functional teams to align modeling outputs with business objectives and risk thresholds.
Translate complex analytical findings into actionable business insights for stakeholders through reports, dashboards, and presentations
Communicate effectively with both technical and non-technical audiences