FinTech Data Analyst (IFRS 9/Credit Risk)

Globik AI; United States; Remote; USD 4,300 - 8,500; Full time

Job summary

Globik AI is seeking a FinTech Data Analyst to translate credit risk model requirements into clear data needs and data-driven solutions. This remote role focuses on borrower, loan, financial, and macro data to support AI model development in financial services.

You will work at the intersection of finance, data science, and AI, collaborating with stakeholders to define data strategy, validate assumptions, and craft high-quality financial datasets for AI applications.

Qualifications

• Minimum 1 year of experience in FinTech, BFSI, or financial data domains.
• Understanding of credit risk concepts: IFRS 9/CECL, PD, LGD, EAD.
• Experience with public datasets, financial/economic data, and synthetic data generation.
• Strong data modeling conceptual knowledge.
• Analytical thinking with ability to question and validate assumptions.
• Excellent written and verbal communication skills.
• Ability to discuss technical concepts with non-technical stakeholders.
• Exposure to banking, lending, or financial regulatory environments.

Responsibilities

• Translate FinTech and credit risk model requirements into clear data needs.
• Break down requirements involving borrower, loan, financial, and macro data.
• Recommend appropriate data approaches: synthetic generation, hybrid datasets, or public/licensed sources.
• Identify and evaluate data sources (Federal Reserve, FDIC, FRED, SEC, industry datasets).
• Define dataset structure, schema, and assist with preparation/validation.
• Participate in client discussions explaining data strategy and methodology.
• Support proposal and documentation creation for data-driven projects.

Skills

Data modeling conceptual knowledge

Analytical thinking

Communication skills

Python

R

Tools

Python

R

Job description

Globik AI is looking for a FinTech Data Analyst with expertise in IFRS 9 and credit risk modeling. This full-time, remote role involves translating FinTech and credit risk model requirements into clear data needs, recommending data approaches, and supporting the development of high-quality financial datasets for AI applications.

You will work at the intersection of finance, data science, and AI - breaking down complex requirements involving borrower, loan, financial, and macroeconomic data to support cutting-edge AI model development in the financial services domain.

Responsibilities

• Translate FinTech and credit risk model requirements into clear data needs
• Break down requirements involving borrower, loan, financial, and macro data
• Recommend appropriate data approaches: synthetic generation, hybrid datasets, or public/licensed sources
• Identify and evaluate data sources (Federal Reserve, FDIC, FRED, SEC, industry datasets)
• Define dataset structure, schema, and assist with preparation/validation
• Participate in client discussions explaining data strategy and methodology
• Support proposal and documentation creation for data-driven projects

Qualifications

• Minimum 1 year experience in FinTech, BFSI, or financial data domains
• Understanding of credit risk concepts: IFRS 9/CECL, PD, LGD, EAD
• Experience with public datasets, financial/economic data, and synthetic data generation
• Strong data modeling conceptual knowledge
• Analytical thinking with ability to question and validate assumptions
• Excellent written and verbal communication skills
• Ability to discuss technical concepts with non-technical stakeholders
• Exposure to banking, lending, or financial regulatory environments

Compensation Structure:

• Fixed Pay: ₹2,00,000 - ₹5,00,000/year
• Variable Pay: ₹2,00,000 - ₹3,00,000/year

Work Schedule: 5 days per week, remote

Preferred Qualifications:

• Experience with Federal Reserve, FDIC, FRED, or SEC datasets
• Background in financial modeling or quantitative analysis
• Familiarity with Python/R for data analysis
• Self-learning ability and adaptability in a fast-paced startup environment

Pay

400-800,000 INR/project