Chief AI/ML Modeling Director

1 week ago


Bengaluru, Karnataka, India WELLS FARGO BANK Full time
About the Role

The Consumer Modeling Development Center, within the Consumer Data, Analytics and AI group, is looking for an experienced AI/ML Modeling Director to lead our team and help us solve complex business problems through data exploration, advanced analytics, and visualization.

  1. Manage teams within the CMDC with varied competencies, including Modeling, Artificial Intelligence, and Gen AI.
  2. Provide technical and thought leadership to the team, performing advanced quantitative and statistical analysis of large datasets to identify trends, patterns, and correlations that can be used to improve business performance.
  3. Oversee the development of predictive modeling algorithms using statistical tools, statistical modeling, optimization, and algorithm development to synthesize large data sets.
  4. Apply critical thinking skills and perform advanced analytics to solve complex and multi-faceted business problems.

Required Qualifications

  • At least 18 years of experience in one or a combination of the following: List Management/Generation, Data Analytics, AI/ML, Predictive Modeling.
  • PhD or master's degree in applied mathematics, statistics, operations research, engineering, physics, accounting, finance, economics, econometrics, computer sciences, or business/social and behavioral sciences with a quantitative emphasis.
  • 12+ years of management experience.

Desired Qualifications

  • 10+ years of Banking, Financial Services Industry, or Consumer business experience in Marketing and CRM.
  • Hands-on industry experience in building large-scale end-to-end machine learning systems using a combination of big data tools and programming languages like Scala, Java, and/or Python.
  • Knowledge of parallel and distributed computing frameworks such as Hadoop, Spark, MPI, using GPUs.

Key Skills

  • Advanced knowledge of machine learning algorithms, including support vector machines, decision trees, logistic regression, clustering, neural networks, and graphical models.
  • Experience in managing a team that interfaces with a broad set of stakeholders across the firm and process/project management.
  • Ability to guide, mentor, and provide technical assistance to the team.


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