Principal Data Scientist

MatchPoint; New York (NY); Hybrid; USD 180,000 - 210,000; Full time

Job summary

A leading recruitment firm is seeking a Principal Data Scientist to design and maintain production machine-learning models in financial services. Candidates should have strong coding skills and experience with banking regulations. This role is hybrid, located in major cities, including New York, and offers a competitive salary range of $180,000 - $210,000 annually.

Qualifications

• Must have experience in production ML models and risk modeling.
• Understanding of banking regulations is necessary.
• Experience triaging model performance issues.

Responsibilities

• Design, build, deploy, and maintain ML models in production.
• Work with cross-functional teams for model deployment.
• Provide leadership and help scale the data science organization.

Skills

PySpark or Scala

Python

SQL

Tools

AWS ML/SageMaker

Job description

This range is provided by MatchPoint. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

$180,000.00/yr - $210,000.00/yr

Direct message the job poster from MatchPoint

Location : On site / Hybrid Cities include: San Francisco CA, New York, Chicago, IL Scottsdale, AZ

Onsite – 30 mins in candidate location

Role Overview : Hands‑on Principal Data Scientist responsible for designing, building, deploying, and maintaining production machine‑learning models in financial services.

Key Responsibilities

• 70–100% hands‑on coding and model development
• Build & deploy ML models into production
• Maintain & triage production models (performance, accuracy, failures)
• Work cross‑functionally with Product, ML, DS, and Customer Analytics teams
• Provide internal and external thought leadership
• Help scale the data science organization
• Work with large datasets (only 1–2 models deployed per year, but high‑impact)

Required Technical Skills Must‑haves

• PySpark or Scala
• Python
• SQL

Industry / Experience Requirements

• Understanding of banking regulations
• Deep experience with production ML models and risk modeling
• Financial services background
• Risk model experience
• Triaging model performance issues
• AWS ML/SageMaker production model deployment

Seniority level

• Executive

Employment type

• Full‑time

Job function

• Finance
• Financial Services and Banking

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