About the roleAttain is seeking a Senior/Staff Data Scientist to support the growing needs of our suite of B2C financial services. This role will be highly hands-on, focused on building, improving, validating, and deploying predictive models that power consumer decisioning and business optimization across our app portfolio.
You will work on advanced machine learning and statistical modeling problems, including cash-flow based credit decisioning for our earned wage advance product, Klover, as well as consumer behavior modeling, transaction categorization, paycheck detection, fraud scoring, churn prediction, and other high-impact predictive modeling use cases. The ideal candidate combines strong quantitative fundamentals with practical experience building models and analytical systems from scratch.
Attain Office Hybrid Schedule: - Chicago, IL: 4 days in-office; 1 day remote
What a typical week might look like- Hands-on development of ML and statistical models at the core of our EWA product, with a focus on fast, rigorous, and high-quality execution
- 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
Preferred Qualifications - 5+ years of direct experience working as a Data Scientist, Machine Learning Scientist, Model Developer, Applied Scientist, Economist, or similar role on relevant business problems
- Strongly preferred: Master's, or Ph.D. in a STEM field such as Computer Science, Statistics, Economics, Mathematics, Engineering, Physics, Operations Research, or a related quantitative field
- Demonstrated ability to apply critical thinking, causal inference, abstract reasoning, and generalization to complex, ambiguous business and technical problems
- Strong expertise developing, validating, deploying, and monitoring machine learning models in production
- Experience with AI/ML-assisted development tools and MLOps practices, including experience working with large language models (LLMs) or autonomous agents for code generation and model refinement
- Experience with predictive modeling, consumer behavior modeling, risk modeling, credit decisioning, fraud modeling, churn modeling, or other high-impact applied ML use cases
- 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
- Demonstrated ability to learn new technologies, applications, and modeling approaches quickly
- Willingness to roll up your sleeves and wear multiple hats across data science, analytics, modeling, and technical execution based on business needs
- Strong written and verbal communication skills, including the ability to explain technical topics to both technical and non-technical audiences
We're excited to hear from you.
At Attain, we are passionate about finding people to continuously help us grow our organization. We encourage you to apply, even if your experience doesn't match every detail of the job description. If we don't see something that immediately fits, we will keep your resume on file for future opportunities.
