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In this role, you will:
Perform highly complex activities related to model development, implementation, and documentation
Required to work individually or as part of a team on multiple data science projects and work closely with business partners across the organization. Mentor and coach budding Data Scientist 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 but not limited to Python, Spark, and H2O etc.
Expert knowledge on working on large datasets using SQL and present conclusions to key stakeholders.
Establish a consistent and collaborative framework with the business and act as a primary point of contact in delivering the solutions.
Experience in building quick prototypes to check feasibility and value to business.
Expert in developing and maintaining modular code-base for reusability
Review and validate models and help improve the performance of the model under the preview of the banking regulations.
Work closely with technology teams to deploy the models to production.
Prepare detailed documentations for projects for both internal and external that complies regulatory and internal audit requirements
Collaborate and consult with regulators, auditors and individuals that are technically oriented and have excellent communication skills
Required Qualifications:
5 - 8 years of relevant hands-on experience in AI/ML model development and Implementation
Bachelor’s/master’s degree in engineering field like computer science, Information technology, Electrical Engineering etc
Master's degree or higher in a quantitative discipline such as mathematics, statistics, engineering, physics, economics, or computer science
Desired Qualifications:
Must have hands on exposure in Python, PySpark and SQL.
Expert knowledge of libraries like sckit-learn, pandas, numpy, mllib, matplotlib, keras…
Expert in data mining and statistical analysis.
Experience in developing, 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
Experience in model deployment, User Acceptance Testing (UAT) and model monitoring.
Hands on knowledge in one or more of Big Data skills – SQL, Aster, Teradata, Hadoop, SPARK, H20, BigQuery.
Exposure to Google Cloud Platform
Critical thinking and strong problem-solving skills.
Ability to learn the business aspects quickly
Knowledge of banking industry and products in at least one of the LOB such as credit cards, mortgage, deposits, loans or wealth management etc.is desirable
Knowledge of functional area such as risk, marketing, operations or supply chain in banking industry is desirable.
Ability to multi-task and prioritize between projects
Ability to work independently and as part of a team
Wells Fargo Recruitment and Hiring Requirements:
b. Wells Fargo requires you to directly represent your own experiences during the recruiting and hiring process.
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