Data Science Manager: Risk Modeling & Production ML

AANCO Financial Services

Philadelphia (Philadelphia County)

On-site

USD 140,000 - 210,000

Full time

14 days+

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Benefits offered by this job

Meaningful equity
Premium health benefits
401k match
Relocation assistance

Job summary

Perpay is seeking a senior Data Science leader to manage a cross‑functional data team, drive end‑to‑end modeling, and align data initiatives with business strategy. You will partner with Engineering, Risk, Marketing, Merchandising, and Finance to deliver production ML solutions and measurable impact.

You will mentor ICs and mid‑career staff, own hiring, and help shape the data science roadmap while advancing risk and credit models in production environments.

Qualifications

  • Minimum 3 years directly managing data scientists and a strong IC background.
  • Experience designing and shipping production ML models end-to-end.
  • Comfort with Python data science stack and cloud tooling.

Responsibilities

  • Lead a Data Science team spanning ICs to senior contributors and own hiring and performance reviews.
  • Set technical strategy and partner with Data Engineering and Strategic Analytics.
  • Ship production models and defend approaches to stakeholders.
  • Collaborate with Risk, Marketing, Finance, and Compliance on data initiatives.

Skills

Python
Data modeling
Machine learning
Leadership
SQL
AWS
R&D collaboration
Communication

Education

Bachelor's degree in a quantitative field
3+ years managing data scientists

Tools

scikit-learn
pandas
NumPy
matplotlib
statsmodels
PyMC
AWS
Airflow
Terraform
Redshift

Job description

Perpay is seeking a senior Data Science leader to manage a cross‑functional data team, drive end‑to‑end modeling, and align data initiatives with business strategy. You will partner with Engineering, Risk, Marketing, Merchandising, and Finance to deliver production ML solutions and measurable impact.

You will mentor ICs and mid‑career staff, own hiring, and help shape the data science roadmap while advancing risk and credit models in production environments.

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