[Hiring] Machine Learning Engineer @Blue Orange Digital

Role Description

We are looking for a Data Scientist or Machine Learning Engineer to join our client's global AI product support team. This scientist will play a critical role in the rollout of our global suite of AI products across consumer lending, business intelligence services, and the health product suite. This role will cover a wide range of responsibilities with plenty of variation from week to week.

• Product development
  • 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
• Client and user support
  • 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
• Testing and QA
  • 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

Qualifications

• 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

Preferred Qualifications

• 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

Benefits

• Fully remote
• Flexible schedule
• Paid parental and bereavement leave
• Worldwide recognized clients to build skills for an excellent resume
• Top-notch team to learn and grow with
• Salary: $5,200 – $5,500 USD monthly