Lead Quantitative Analytics Specialist
Wells Fargo · Bengaluru · onsite · Posted 68d ago
Undisclosed5–10 yrsfulltimeSourced from
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About this role
Job Summary
About this role: Wells Fargo is seeking a Lead Quantitative Analytics Specialist.
Responsibilities - Lead complex initiatives including creation, implementation, documentation, validation, articulation, and defense of highly statistical theory
- Qualify monitor markets and forecast credit and operational risks
- Strategize short and long-term objectives, and provide analytical support for a wide array of business initiatives
- Utilize stochastic, structured securities, spread analysis, with the expertise in the theory and mathematics behind the analysis
- Review and assess models inclusive of technical, audit, and market perspectives
- Identify structure and scope of review
- Enable decision making for product and marketing with broad impact and act as key participant to develop and document analytical models
- Collaborate and consult with regulators and auditors
- Present results of analysis and strategies
- 5+ years of Quantitative Analytics experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
- Bachelor's degree or higher in a quantitative discipline such as mathematics, statistics, engineering, physics, economics, or computer science
- Overall experience around 5+ years in similar role
- Bachelors degree or higher in a quantitative field such as Computer Science, Applied mathematics, engineering, statistics, finance or econometrics from top tier institutes
- Strong problem-solving skills
- 5+ years of experience in credit risk analytics with exposure to statistical and machine learning model development, implementation or ML Ops
- 2+ years of advanced programming expertise in SAS
- 5+ years of advanced programming and debugging skills in Python OOP, packaging, build and deployment, data structures and algorithms, decorators, logging, exception handling, JIT compilers
- 2+ years of experience in High performance computing, Big Data and real time solutions PySpark, MapR streaming, parallel processing, real time optimization.
- 2+ years of experience in unit testing, UAT testing, regression testing and code review
- Comfortable with Git, GitHub, CI/CD pipelines and UNIX commands
- Excellent verbal, written, and interpersonal communication skills
- Strong ability to develop partnerships and collaborate with other business and functional areas
- Knowledge and understanding of issues or change management processes
- Experience determining root cause analysis
- Detail oriented, results driven, and has the ability to navigate in a quickly changing and high demand environment while balancing multiple priorities
- Understanding of bank regulatory data sets and other industry data sources
- Ability to research and report on a variety of issues using problem solving skills
- Exposure to banking domain in Credit Risk area on Retail/Commercial portfolio
- Implement optimized ML solutions
- Perform various complex activities related to predictive modeling process enhancements and Python conversions
- Provide engineering and analytical solutions across model development, implementation, monitoring and production in a Big Data environment
- Support implementation of python based solutions for real time and/or batch based Machine Learning scorecard models for consumer and commercial banking
- Identify opportunities and deliver process improvements, standardization, rationalization and automations
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Skills
Code ReviewCI/CD PipelinesBanking domainChange ManagementAnalyticsApplied MathematicsBankingCompilersCommercial BankingData Structurescredit riskCommunication SkillsAlgorithmscomplianceCustomer RelationshipsBig Data
About Wells Fargo
Wells Fargo
Financial Services
20k+
employees
1852
174 years old
Bengaluru/Bangalore, Karnataka
India
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Wells Fargo works to create positive social impact in the communities it serves by supporting housing affordability, small business growth, financial health, and a low-carbon economy.
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