Machine Learning Engineer
Company overview:
Blue Orange Digital is a boutique data & AI consultancy that delivers enterprise‑grade results. We design and build modern data platforms, analytics, and ML/AI Agent solutions for mid‑market and enterprise clients across Private Equity, Financial Services, Healthcare, and Retail.
Our teams work with technologies like Databricks, Snowflake, dbt, and the broader Microsoft ecosystem to turn messy, real‑world data into trustworthy, actionable insight.
We’re a builder‑led, client‑first culture that prizes ownership, clear communication, and shipping high‑impact work.
Note: Please submit your resume in English, as all application materials must be in English for review and consideration.
Position overview:
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.
Responsibilities will include, but are not limited to:
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
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
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
Background checks may be required for certain positions/projects
Blue Orange Digital is an equal‑opportunity employer
- Department
- Engineering
- Role
- Machine Learning Engineer
- Locations
- São Paulo, Remote - LATAM, Santiago, Mexico City, Buenos Aires
- Remote status
- Fully Remote
- Monthly salary
- $5,200 - $5,500
About Blue Orange Digital
Blue Orange Digital is a data and AI consulting firm that helps companies turn complex data into real business outcomes. We partner with organizations across industries to design and deploy scalable data infrastructure, advanced analytics, and AI-powered solutions. Our team is fully remote, globally distributed, and driven by curiosity, impact, and innovation.