Blue Orange DigitalRemote
Machine Learning Engineer
United States of America
Full Time
3 weeks ago
$5,200 - $5,500 USD
Visa Sponsor
Key skills
SQLSpark SQLPythonJupyter notebooksMLlibPyTorchsklearnTensorFlowCredit risk modelingData visualizationData engineeringCredit risk assessment toolsGrowth mindsetAIMachine LearningMLJupyterETLData EngineeringAnalyticsBISparkCommunication
About this role
Blue Orange Digital is a boutique data & AI consultancy that delivers enterprise‑grade results. They are looking for a Machine Learning Engineer to join their global AI product support team, responsible for product development, client support, and testing of AI products across various sectors.
Responsibilities:
- Prototype new modeling methodologies for incorporation into our global suite
- Work directly with our ML engineering team to identify issues and guide them on requirements
- Write data pipelines and ETL for non‑standard or new modeling use cases
- Build new dashboards and reports to provide insights to clients on model performance and impact, leveraging our proprietary BI toolkit
- Help document methodologies, tool usage, and business logic
- Support client implementation teams executing complex modeling tasks on our enterprise ML ops platform
- Perform complex or custom data engineering where needed to support strategic clients
- Train ML models for underwriting, targeting, and other applications where needed
- Test new product features and algorithms, and verify accurate implementation ahead of live release to our global client base
- Implement bug fixes and upgrades to Experian methodologies in credit‑related business logic, including Bureau Inferencing modifications
Requirements:
- Highly proficient in writing data processing code with at least one SQL dialect, Spark SQL experience desirable but not required
- Comfortable using Python and Jupyter notebooks with common open‑source ML libraries such as MLlib, PyTorch, sklearn, and TensorFlow
- Understanding of credit risk modeling fundamentals
- Strong communication skills with both business and technical audiences
- Strong data visualization skills
- Self‑starter with a growth mindset
- Experience in modeling or data engineering within a Credit Risk institution, typically three to five years at a major bank, FinTech, or financial institution
- Five to seven years of total industry experience in analytics, data science, or data engineering
- Bachelor's degree required; Master's degree preferred
- Familiarity with credit risk assessment tools such as FICO Model Builder and SAS
- Understanding of the credit risk lifecycle from prospecting and acquisition to customer management and collections