Risk - Data Analytics - Operational Risk Management and Analysis - Associate - Bengaluru
The Risk division is responsible for credit, market and operational risk, model risk, independent liquidity risk, and insurance throughout the firm .
Operational Risk Management & Analysis
The Operational Risk Management and Analysis department, an independent risk management function, is responsible for developing and implementing a standardized framework to identify, measure, and monitor operational risk across the firm.
Description of the Role
The candidate will be part of a team in Bengaluru which has primary responsibility for operational risk data quality, aggregation and analytics. Additionally, the candidate will be responsible for developing and participating in risk data initiatives that will support global operational risk management functions.
RESPONSIBILITIES AND QUALIFICATIONS
The responsibilities include:
- Develop key operational risk indicators from different sets of disparate datasets and identify common patterns between them using different Machine Learning Techniques
- Derive insights by a combination of structured and unstructured data analysis. This would require a deep expertise in analyzing the unstructured data through various Natural Language Processing techniques
- Performing anomaly detections on large diverse data sets to understand the reasons for a control failure
- Develop classification techniques to understand the themes emerging from historical risk events and identify the causal factors for the same
- Engage directly with senior leadership to understand strategy, assess new activities, enforce limits, comply with regulatory requirements, and challenge existing methodologies
- Provide advisory support; identifying and testing new quantitative risk measures
In performing the job function, you will have the following opportunities:
- As the division invests in and matures the function, the role will provide first-hand experience to build a word class quantitative team from scratch
- Exposure to challenging quantitative problems such as quantifying operational risks across the firm, globally
- Development of quantitative and programming skills as well as product and risk knowledge
- Involvement in critical internal risk management practices, and provision of data to both internal and external stakeholders
- Opportunities to work with other groups in various areas of the firm
- Dynamic team work environment
Qualifications, Skills & Aptitude
- Degree in a quantitative field such as Mathematics, Physics, Statistics or Engineering
- Basic applied statistics, Machine learning techniques (Supervised / Unsupervised Techniques)
- Strong programming skills in at least one programming language (R/ Python / Java / C++)
- Strong problem and analytical solving skills are required
- Prior experience in Natural Language Processing Techniques is preferred
- Experience with data visualization toolsets (such as Tableau, Spotfire, QlikView, or R Shiny) is an added advantage
- Strong written and verbal communication skills
- Self-motivated team player
ABOUT GOLDMAN SACHS
The Goldman Sachs Group, Inc. is a leading global investment banking, securities and investment management firm that provides a wide range of financial services to a substantial and diversified client base that includes corporations, financial institutions, governments and individuals. Founded in 1869, the firm is headquartered in New York and maintains offices in all major financial centers around the world.
© The Goldman Sachs Group, Inc., 2018. All rights reserved Goldman Sachs is an equal employment/affirmative action employer Female/Minority/Disability/Vet.
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The Goldman Sachs Group, Inc. is a leading global investment banking, securities, and investment management firm that provides a wide range of financial services to a substantial and diversified client base that includes corporations, financial institutions, governments, and individuals. Founded in 1869, the firm is headquartered in New York and maintains offices in all major financial centers around the world.
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