Remote Financial Data Analyst: ECL & Macro Insights

Globik AI; United States; Remote; USD 146,000 - 293,000; Full time

Job summary

Globik AI is hiring a Financial Data Analyst to research and extract macroeconomic indicators, design and validate synthetic borrower profiles, and map financial variables to ECL compliance. This full-time, remote position requires strong financial acumen and mathematical aptitude in a fast-paced startup.

You will coordinate with AI and data engineering teams on technical requirements and independently manage end-to-end task execution with minimal supervision.

Qualifications

• Minimum 1 year of relevant financial data analytics experience.
• Experience with US-based financial data or regulatory reporting preferred.
• Finance/economics/accounting credentials preferred (CFA/FRM/CA-Inter).
• Background in credit risk analysis.
• Excellent English proficiency (written and verbal).
• Strong mathematical aptitude and attention to detail.
• Tech-savvy with ability to learn new data tools quickly.
• Ability to work independently in a remote, fast-paced startup.

Responsibilities

• Research and extract macroeconomic indicators from authoritative sources.
• Design and validate synthetic borrower profile logic for US market distributions.
• Map financial variables to ECL framework compliance.
• Perform mathematical validations on generated financial datasets.
• Coordinate with AI and data engineering teams on technical requirements.
• Independently manage end-to-end task execution with minimal supervision.

Tools

Python

R

Tableau

Power BI

Bloomberg

Reuters

Job description

Globik AI is hiring a Financial Data Analyst to research and extract macroeconomic indicators, design and validate synthetic borrower profiles, and map financial variables to ECL compliance. This full-time, remote position requires strong financial acumen and mathematical aptitude in a fast-paced startup.

You will coordinate with AI and data engineering teams on technical requirements and independently manage end-to-end task execution with minimal supervision.