Job
Description
About this role: Wells Fargo is seeking a Senior Lead Data Science Consultant... Position requires a Bachelors / Masters degree in Mathematics, Statistics, or related quantitative field and four 10+ years of experience in the job offered or in a related quantitative analytics role. Specific skills required: Quantitative experience with credit risk, loss forecasting or stress testing methodologies; Experience validating macro-economic scenario forecasts; Experience with the development and oversight of methodologies used in commercial modeling, investment securities, and economic modeling; Strong quantitative skills with a background in mathematical and/or statistical techniques used in stress test modeling such as logistic regression, Monte Carlo simulation, time series modeling, machine learning, and hazard modeling; Programming skills with strong experience in model development and performance testing methodology using SAS, Python, R, or other statistical software; Business acumen with the ability to engage diverse stakeholders for the planning and completing of complex model validation projects independently and effectively; and Develop best-in-class transactional and application risk models leveraging cutting-edge advanced AI/ML techniques Lead and participate in critical debugging, testing and performance tuning for machine learning and/or statistical models written in python code Conduct ad-hoc analysis and reporting as required Responsible for documenting and presenting detailed model development processes and results, suitable for a variety of audiences Lead and participate intensive team discussions, interactions with cross-functional teams, and dialogues with internal reviewers (Model Validation and Internal Audit) Collaborate with key business model users to ensure models are business driven, properly implemented and executed Respond to ongoing analytical requests from auditors and regulatory reviewers in timely manner Essential Skills: 10+ years of analytics experience with experience in customer call analytics and escalated complaints analytics. Master's degree or higher in a quantitative field such as mathematics, statistics, engineering, physics, economics, or computer science 10+ years of programming experience in SAS, Python, Tableau & ThoughtSpot. Experience in LLM/Topic Modelling & ML model development and/or monitoring Excellent verbal and written communication skills Experience in producing high quality technical documentation with tools such as Excel, Word, PowerPoint Desired Skills: Bachelors/Masters in Analytics or similar quantitative disciplines Experience in statistical modeling techniques Exposure to machine learning techniques (Random Forest, XG Boost, Light GBM, Neural Networks, LLM and so on) Developed Fraud Risk Model using Python or other vendor based tools Excellent problem solving skills and ability to connect dots, see big picture and find solutions and articulate in a clear manner. Understanding of process, methodologies used in credit/fraud scoring model development, implementation, validation and monitoring Ability to effectively manage multiple assignments with challenging timelines
