OneMain Financial Jobs

Full Stack Data Scientist

Req number:

R7107

Employment type:

Full time

Worksite flexibility:

Remote

Who we are

CAI is a global services firm with over 9,000 associates worldwide and a yearly revenue of $1.3 billion+. We have over 40 years of excellence in uniting talent and technology to power the possible for our clients, colleagues, and communities. As a privately held company, we have the freedom and focus to do what is right—whatever it takes. Our tailor-made solutions create lasting results across the public and commercial sectors, and we are trailblazers in bringing neurodiversity to the enterprise.

Job Summary

As the Full Stack Data Scientist, you will be responsible for building, deploying, and managing machine learning models, partnering with stakeholders to solve business problems, and ensuring the operational success of productionized ML systems.

Job Description

We are looking for a Full Stack Data Scientist to lead the design, development, deployment, and lifecycle management of machine learning models across production systems. This position will be full-time and remote.

What You’ll Do

Translate business problems into ML solutions that move metrics

• Partner with stakeholders and SMEs to understand the domain, convert real problems into analytical form, and select the right methodology (ML, statistics, optimization, simulation)

• Define success metrics, evaluation approaches, and validation plans (including baseline comparisons and monitoring strategy)

Build high-quality ML models (the “real data science” part)

• Design, develop, and iterate on models (forecasting, regression, classification, clustering, anomaly detection, etc.) with strong feature engineering and disciplined experimentation

• Deliver clear, decision-ready insights and communicate methods/results to technical and non-technical audiences

Engineer models into production (the “ML Engineer” part)

• Productionize prototypes into robust ML systems with appropriate error handling, versioning, reproducibility, and deployment patterns

• Build and maintain automated pipelines for training/validation/deployment, with CI/CD practices designed for ML workflows

• Use AWS (SageMaker) and Databricks to operationalize training and inference workflows, with a clean separation of data engineering, feature engineering, and model logic.

Own model lifecycle management (tracking, registry, governance)

• Track experiments and manage model artifacts with MLflow, operating a disciplined model promotion process (e.g., staging to production)

• Leverage a model registry as a centralized system for model lineage/versioning and lifecycle management.

Operate production ML (monitoring, alerts, and continuous improvement)

• Implement observability across model and data health: drift detection, performance regression, and actionable alerts with runbooks

• Support and enhance existing production models (new features, improvements, reliability hardening), driving continuous improvement post-deployment.

What You'll Need

Required:

• Demonstrated hands-on experience building ML models and deploying/operating them in production (end-to-end ownership)

• Strong Python skills; ability to write clean, testable, maintainable code (refactoring, modularity, code review discipline)

• Experience with distributed data/ML workloads in PySpark and strong SQL/data wrangling capability

• Practical experience with AWS, especially SageMaker, and experience delivering ML workloads on Databricks

• Experience with MLflow for experiment tracking and model lifecycle workflows

• Strong communication skills and the ability to collaborate across functions to embed analytics into business processes

Preferred:

• Experience implementing CI/CD for ML systems (tests, data/contract checks, packaging, automated deployments)

• Experience with model monitoring/drift tooling and defining retraining triggers tied to business SLAs

• Experience with modern ML frameworks (e.g., PyTorch/TensorFlow) and GenAI/LLM workflows

• Manufacturing/industrial analytics exposure (quality, supply chain, pricing, forecasting).

Physical Demands

• Ability to safely and successfully perform the essential job functions

• Sedentary work that involves sitting or remaining stationary most of the time with occasional need to move around the office to attend meetings, etc.

• Ability to conduct repetitive tasks on a computer, utilizing a mouse, keyboard, and monitor

Reasonable accommodation statement

If you require a reasonable accommodation in completing this application, interviewing, completing any pre-employment testing, or otherwise participating in the employment selection process, please direct your inquiries to application.accommodations@cai.io or (888) 824 – 8111.