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Lead Quantitative Analytics Specialist

https://www.wellsfargo.com/ Logo

Wells Fargo

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Location:
India, Bengaluru

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Category:
Finance

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Contract Type:
Employment contract

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Salary:

Not provided
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Job Description:

Wells Fargo is seeking a Lead Quantitative Analytics Specialist. The role involves the development, implementation, and validation of advanced analytical models, providing analytical support, creating modular code bases, and aligning initiatives compliant with banking regulations. Applicants are expected to have advanced qualifications in quantitative disciplines, strong programming skills, and expertise in machine learning, statistical models, and big data tools.

Job Responsibility:

  • 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
  • Mentor and coach budding Data Scientists on developing and implementing data science solutions
  • Perform various complex activities related to statistical/machine learning
  • Provide analytical support for developing, evaluating, implementing, monitoring, and executing models across business verticals using emerging technologies including Python, Spark, and H2O
  • Build quick prototypes to check feasibility and value to business
  • Develop and maintain modular code-base for reusability
  • Review and validate models and help improve their performance under the preview of banking regulations
  • Work closely with multiple teams such as technology, ML Ops, MRM teams to deploy models to production
  • Prepare detailed documentation for projects for both internal and external stakeholders complying with regulatory and internal audit requirements
  • Mentor and guide junior team members and work on multiple analytics/data science initiatives

Requirements:

  • 5+ years of Quantitative Analytics experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
  • Master's degree or higher in a quantitative discipline such as mathematics, statistics, engineering, physics, economics, or computer science
  • PhD in statistics/economics/mathematics/operations research or similar is mandatory
  • 3+ years of hands-on exposure in Python, PySpark and SQL
  • Expert knowledge of libraries like scikit-learn, pandas, numpy, mllib, matplotlib, keras
  • Expert in data mining and statistical analysis
  • 5+ years of experience in developing and implementing models
  • Statistical models – linear regression, logistic regression, time series analysis, multivariate statistical analysis
  • Machine learning models – Random Forest, XGBoost, GBM, SVM
  • Exposure to deep learning framework - ANN, RNN, CNN, LSTM
  • Excellent understanding of model metrics including AUC, ROC, F-statistics etc. with clear understanding of how model performance is tuned
  • Strong programming skills
  • Hands-on knowledge in one or more Big Data skills – SQL, Aster, Teradata, Hadoop, SPARK, H2O, Big Query
  • Exposure to Google Cloud Platform
  • Critical thinking and strong problem-solving skills
  • Ability to learn the business aspects quickly and handle multiple projects

Nice to have:

  • Knowledge of banking industry and products in at least one line of business such as credit cards, mortgage, deposits, loans, or wealth management
  • Knowledge of functional areas such as risk, marketing, operations, or supply chain in the banking industry
  • Working expertise in Tensorflow, Keras, or Pytorch
  • Working knowledge in developing end-to-end AI/ML pipeline in Apache Spark, Sparkling Waters, H2O, Caffe in Hortonworks/Cloudera/MapR or Teradata Aster big data platforms
  • Ability to work with Data Engineers in discovering and optimizing bottlenecks in the AI/ML pipeline for real-time or near-real-time applications that consume large throughput of data

Additional Information:

Job Posted:
May 30, 2025

Expiration:
June 05, 2025

Employment Type:
Fulltime
Work Type:
On-site work
Job Link Share:
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