Staff Data Scientist (Fintech)

TL;DR

Staff Data Scientist (Fintech): Owning the full machine learning model development lifecycle from conception to deployment for credit risk models and paycheck detection algorithms with an accent on credit products like hirify.global Cash Advance and Thrive Line of Credit. Focus on building predictive models to decrease loss rates, increase approval rates, and drive business growth through underwriting, marketing, and fraud strategies.

Location: Remote - US

Salary: $185K – $230K

Company

Mobile-first fintech using machine learning-powered credit models with over 250 real-time financial signals to serve millions of customers worldwide.

What you will do

• Grow user base and retention through machine learning models and analytics on large-scale datasets.
• Build and deploy ML models for credit risk, paycheck detection, underwriting, marketing, fraud, and customer experience.
• Collaborate with engineering to implement models in production and with product/operations for strategic alignment.
• Develop data standards and analytics pipelines to support ongoing analysis.

Requirements

• BS in engineering, computer science, finance, or mathematics.
• 6+ years in data mining, machine learning, statistical analysis, or predictive modeling.
• Deep knowledge of statistics/ML techniques (regression, classification, clustering, optimization) and building models from scratch.
• Strong Python and intermediate/advanced SQL; experience with scikit-learn, LightGBM, XGBoost, SparkML.
• Comfort with cross-functional collaboration and strong problem-solving/communication skills.

Nice to have

• Knowledge of deep learning and DL toolkits (Tensorflow, Keras, PyTorch).

Culture & Benefits

• Remote-first with WFH office reimbursement and paid global onsites twice yearly.
• Competitive pay with equity and bonus; flexible health plans with subsidies.
• Direct leadership exposure, growth based on contributions, and collaborative environment across 14 countries/12 time zones.
• Emphasis on excellence, impact, mutual respect, and work-life balance.