Job Description
Main Purpose:
Data engineering - Source data from internal system sources and external (public/private) sources, using data pipelines or automations
Data science & risk modelling - Develop risk models / algorithm for calculating credit scoring of clients, credit loss, simulating stress scenarios and LLM models to aide credit risk assessment
Risk Reporting & Visualization - Develop risk reports and dashboards for credit risk officers to analyse and monitor risks in their portfolio
Data governance - Organise and document data attributes, process and procedures
Infrastructure management - Collaborate with internal technology teams to analyse impact on data due to infrastructure changes
To understanding trade Life Cycle – work closely with key departments across the organization, including Accounting, Trade Finance, Operations, and Deal Desk (amongst others) to understand data throughout the trade life cycle
Knowledge Skills and Abilities, Key Responsibilities:
Bachelor’s degree in computer science, Finance, Mathematics, Statistics, or related field
3-5 years of experience in data engineering, data science, or similar technical role
Proficiency in SQL and database management systems
Strong programming skills in Python, R, or similar languages for statistical analysis and machine learning
Experience with machine learning frameworks (scikit-learn, TensorFlow, PyTorch)
Knowledge of statistical modeling, econometrics, and risk management methodologies
Experience with ETL/ELT tools and data pipeline frameworks
Familiarity with Large Language Models and Natural Language Processing techniques
Experience with data visualization tools (Tableau, Power BI, or similar)
Excellent English verbal and written communication
Key Responsibilities:
Data Engineering:
Design, build, and maintain robust data pipelines to source data from internal system sources and external public/private data providers
Develop automated data ingestion processes to ensure timely and accurate data flow
Implement data quality controls and monitoring systems to maintain data integrity
Data Science & Risk Modelling:
Develop and maintain sophisticated risk models and algorithms for calculating client credit scores
Build predictive models for credit loss estimation and expected credit loss calculations
Design and implement stress testing scenarios to evaluate portfolio resilience under adverse conditions
Create and deploy Large Language Model (LLM) solutions to enhance credit risk assessment processes
Risk Reporting & Visualization:
Develop comprehensive risk reports and interactive dashboards for credit risk officers
Create visualization tools that enable effective portfolio risk analysis and monitoring
Data governance:
Organise and document data attributes, process and procedures
Infrastructure management:
Collaborate with internal technology teams to analyse impact on data due to infrastructure changes
Trade Life Cycle:
Work closely with key departments across the organization, including Accounting, Trade Finance, Operations, and Deal Desk (amongst others) to understand data throughout the trade life cycle
Key Relationships
Global Credit team, risk technology, data scientist, Other internal departments (accounts, treasury, trade finance, operations etc)
Key Relationships and Department Overview:
Global Credit team, Head of Operation Risk Management, Other internal departments (accounts, treasury, trade finance, operations etc)
Data engineering - Source data from internal system sources and external (public/private) sources, using data pipelines or automations
Data science & risk modelling - Develop risk models / algorithm for calculating credit scoring of clients, credit loss, simulating stress scenarios and LLM models to aide credit risk assessment
Risk Reporting & Visualization - Develop risk reports and dashboards for credit risk officers to analyse and monitor risks in their portfolio
Data governance - Organise and document data attributes, process and procedures
Infrastructure management - Collaborate with internal technology teams to analyse impact on data due to infrastructure changes
To understanding trade Life Cycle – work closely with key departments across the organization, including Accounting, Trade Finance, Operations, and Deal Desk (amongst others) to understand data throughout the trade life cycle
Knowledge Skills and Abilities, Key Responsibilities:
Bachelor’s degree in computer science, Finance, Mathematics, Statistics, or related field
3-5 years of experience in data engineering, data science, or similar technical role
Proficiency in SQL and database management systems
Strong programming skills in Python, R, or similar languages for statistical analysis and machine learning
Experience with machine learning frameworks (scikit-learn, TensorFlow, PyTorch)
Knowledge of statistical modeling, econometrics, and risk management methodologies
Experience with ETL/ELT tools and data pipeline frameworks
Familiarity with Large Language Models and Natural Language Processing techniques
Experience with data visualization tools (Tableau, Power BI, or similar)
Excellent English verbal and written communication
Key Responsibilities:
Data Engineering:
Design, build, and maintain robust data pipelines to source data from internal system sources and external public/private data providers
Develop automated data ingestion processes to ensure timely and accurate data flow
Implement data quality controls and monitoring systems to maintain data integrity
Data Science & Risk Modelling:
Develop and maintain sophisticated risk models and algorithms for calculating client credit scores
Build predictive models for credit loss estimation and expected credit loss calculations
Design and implement stress testing scenarios to evaluate portfolio resilience under adverse conditions
Create and deploy Large Language Model (LLM) solutions to enhance credit risk assessment processes
Risk Reporting & Visualization:
Develop comprehensive risk reports and interactive dashboards for credit risk officers
Create visualization tools that enable effective portfolio risk analysis and monitoring
Data governance:
Organise and document data attributes, process and procedures
Infrastructure management:
Collaborate with internal technology teams to analyse impact on data due to infrastructure changes
Trade Life Cycle:
Work closely with key departments across the organization, including Accounting, Trade Finance, Operations, and Deal Desk (amongst others) to understand data throughout the trade life cycle
Key Relationships
Global Credit team, risk technology, data scientist, Other internal departments (accounts, treasury, trade finance, operations etc)
Key Relationships and Department Overview:
Global Credit team, Head of Operation Risk Management, Other internal departments (accounts, treasury, trade finance, operations etc)
💡 Quick Summary
Seeking a career-building opportunity? The Credit Support Analyst position is now open for candidates interested in the Accountant Jobs sector. This role in Mumbai offers a professional environment and growth potential.
Requirement Snapshot: Candidates should possess basic communication skills, a proactive attitude, and the ability to work in a team. Experience in Accountant Jobs is a plus.