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Torentify · Dallas, TX

Data Scientist - Hybrid

Hybridentry_levelfull time$130,000 – $145,000 / yearPosted yesterday
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About the Role

Harnham is seeking a Lead Data Scientist to drive advanced risk and financial modeling initiatives that directly support business performance. This is a highly visible individual contributor role for an experienced data scientist who can independently lead complex projects, quantify business impact, and communicate analytical findings effectively to senior and executive stakeholders.

The role focuses on identifying financial opportunities, developing predictive and risk models, and delivering measurable business outcomes. The successful candidate will combine advanced technical expertise with business understanding and the ability to support model governance and defend analytical models in regulated environments.

Key Responsibilities

Lead end-to-end data science projects from problem definition through implementation.

Develop, validate, and monitor predictive and risk models using large-scale financial and customer datasets.

Apply advanced statistical and machine learning techniques, including gradient boosting models.

Translate model outputs into actionable business recommendations and quantified financial impact.

Present analytical findings, model performance, and recommendations to senior leadership and executive stakeholders.

Support model governance activities, audits, and validation reviews.

Independently own complex analytical projects and ensure successful delivery.

Mentor and support team members while serving as a technical leader within the organization.

Required Qualifications

6–8+ years of experience in data science, quantitative analytics, or predictive modeling.

Strong background in finance, credit, or risk modeling within a regulated industry.

Advanced proficiency in Python and SQL.

Strong foundation in mathematics, statistics, and predictive modeling.

Experience building and validating models used for financial or risk-related decision-making.

Experience presenting technical concepts and model results to executive audiences.

Demonstrated ability to independently manage and deliver complex projects.

Experience supporting external audits and defending analytical models.

Preferred Experience

Experience in one or more of the following areas is preferred:

Credit risk modeling

Probability of Default (PD) modeling

Credit loss and loss forecasting models

Scorecard development

Payment behavior analytics

Banking, lending, mortgage, or credit card data

Credit bureau data

Financial impact and portfolio analysis

Education

Required:

Bachelor's degree in Mathematics, Statistics, Economics, Computer Science, Engineering, or another quantitative discipline.

Preferred:

Master's degree in Data Science, Statistics, Mathematics, Economics, Engineering, or a related quantitative field.

Technical Skills

Python

SQL

Statistical Modeling

Predictive Modeling

Machine Learning

Gradient Boosting

Risk Modeling

Financial Modeling

Credit Analytics

Portfolio Analysis

Data Science

Ideal Candidate Profile

The ideal candidate is a senior-level data scientist who can independently take ownership of complex modeling initiatives while connecting technical results to measurable business outcomes. You should be comfortable working with financial and customer datasets, developing models for risk-related decisions, and explaining technical methodologies and results to executive stakeholders.

Strong business acumen, analytical rigor, and experience working within regulated environments are important for this position.

Why Join?

Direct ownership of high-value analytics initiatives.

Opportunity to see models implemented and connected to measurable business outcomes.

Significant exposure to senior and executive stakeholders.

Collaborative environment where individual technical contributions have high visibility.

Opportunity to work on projects designed to identify and deliver significant financial opportunities.

Work Schedule

This is a hybrid position requiring four days onsite per week, Monday through Thursday. Tempe, Arizona is the preferred location, with Dallas, Texas and Atlanta, Georgia also being considered.

Compensation

The position offers a base salary of $130,000–$145,000 per year, plus eligibility for a bonus.

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