# Senior/Staff Data Scientist

**Company:** [Attain](https://hotfix.jobs/companies/attain)
**Location:** Chicago, IL
**Role:** Data Science
**Experience:** 5+ years
**Skills:** Python, SQL, Machine Learning, Statistical Modeling, Feature Engineering, Model Deployment, MLOps, GCP, Data Exploration, Model Evaluation
**Posted:** 2026-05-03

> Senior/Staff Data Scientist building and deploying predictive ML models for consumer fintech products including credit decisioning, fraud detection, and churn prediction. Owns full model lifecycle from data exploration to production monitoring.

## Job Description

## Responsibilities
- Hands-on development of ML and statistical models at the core of our EWA product
- Build and improve predictive models across consumer decisioning, consumer behavior modeling, fraud, churn, transaction intelligence, and other business-critical use cases
- Own the full model development lifecycle, including data exploration, feature engineering, model training, validation, deployment, monitoring, and retraining
- Develop reusable modeling pipelines, analytical tools, and production-quality code to support scalable data science work
- Apply strong statistical and mathematical judgment to model evaluation, calibration, robustness testing, and business impact measurement
- Collaborate with data analysts, engineers, product managers, and business stakeholders to deliver ML models with quality, efficiency, and precision
- Identify new areas where data science, predictive modeling, and optimization can improve product and business outcomes

## Requirements
- 5+ years of direct experience working as a Data Scientist, Machine Learning Scientist, Model Developer, Applied Scientist, Economist, or similar role
- Strong expertise developing, validating, deploying, and monitoring machine learning models in production
- Solid foundation in statistics, probability, mathematics, and machine learning fundamentals
- Strong Python coding skills, with the ability to build models, pipelines, and analytical tools from scratch
- Strong SQL skills and experience working with large, messy, real-world datasets
- Experience with feature engineering, model evaluation, calibration, monitoring, retraining, and model performance diagnostics
- Experience with cloud computing services or platforms (GCP preferred)
- Familiarity with version control, peer code review, and collaborative software development practices

## Nice-to-Haves
- Master's or Ph.D. in a STEM field such as Computer Science, Statistics, Economics, Mathematics, Engineering, Physics, Operations Research
- Experience with AI/ML-assisted development tools and MLOps practices, including LLMs or autonomous agents
- Experience with predictive modeling, consumer behavior modeling, risk modeling, credit decisioning, fraud modeling, churn modeling
- Demonstrated ability to learn new technologies quickly
- Strong written and verbal communication skills

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