Explore 1M+ Live Opportunities.
Direct applications, high-package MNC listings, and exclusive insider referrals updated daily across 50+ niches worldwide.
Direct applications, high-package MNC listings, and exclusive insider referrals updated daily across 50+ niches worldwide.
Harnham · Tempe, Arizona
Lead Data Scientist | Financial Risk & Advanced Analytics
Tempe, AZ (Preferred) | Dallas, TX | Atlanta, GA
Hybrid (4 days onsite, Monday-Thursday)
$140,000-$150,000 Base Salary
US Citizens & Green Card Holders Only
Are you looking for a role where your models don't sit on a shelf?
A highly respected organization is seeking a Lead Data Scientist to tackle complex financial risk problems, uncover multi-million-dollar business opportunities, and deliver analytics that directly influence executive decision-making. This is a high-visibility position where your work will be implemented, measured, and tied directly to business outcomes.
If you're someone who enjoys owning projects end-to-end, defending your analytical thinking, and seeing your work create measurable financial impact, this opportunity offers a rare combination of technical depth, business influence, and autonomy.
Lead the development of predictive and quantitative models that drive critical business decisions.
Analyze large-scale financial and credit-related datasets to identify opportunities and risks.
Build, enhance, validate, and defend sophisticated risk models within a regulated environment.
Translate complex model outputs into clear financial recommendations and measurable business value.
Partner directly with senior leadership and executive stakeholders to present findings and influence strategy.
Own projects from initial problem definition through deployment and business adoption.
Support external audits and confidently explain model methodology, performance, and governance.
What We're Looking For
8+ years of Data Science, Quantitative Analytics, Risk Analytics, or Modeling experience.
Strong foundation in statistics, mathematics, econometrics, or quantitative modeling.
Experience building machine learning models, including gradient boosting techniques.
Proven experience owning projects independently and delivering business results.
Strong communication skills with the ability to present technical concepts to non-technical executives.
Experience operating within regulated environments and supporting model audits.
Required Domain Experience
Candidates must have experience in financial or risk modeling environments, including areas such as:
Credit Risk Modeling
Probability of Default (PD) Modeling
Loss Forecasting or Credit Loss Assessment
Financial Risk Analytics
Scorecard Development
Payment Behavior Modeling
Credit Attribute Modeling
Banking, Lending, Credit Bureau, Mortgage, or Consumer Finance Analytics
Bachelor's degree in a quantitative discipline such as:
Mathematics
Statistics
Economics
Computer Science
Engineering
Related quantitative field
Master's degree in Data Science, Statistics, Applied Mathematics, Economics, or a similar quantitative field is highly preferred.
Why This Opportunity Stands Out
Unlike many Data Science positions, the impact here is immediate and visible.
You'll join a lean, high-performing team responsible for identifying and delivering opportunities worth millions of dollars annually. Leadership places significant value on data-driven decision-making, and the right person will have direct exposure to executives while maintaining ownership of mission-critical initiatives.
Ideal Candidate
This role is perfect for a senior individual contributor or lead-level data scientist who enjoys solving complex financial problems, building production-ready models, proving business value through analytics, and operating as a trusted strategic partner to leadership.
Confidential search. Qualified candidates will be contacted directly for additional details.
Base Salary: $140,000-$150,000 + comprehensive benefits
Details
| Company | Harnham |
| Location | Tempe, Arizona |
| Type | FULL TIME |
| Niche | Full-time |
| Salary | $1,40,000 – $1,40,000 / yr |