Senior Quantitative Analytics Specialist

Wells Fargo seeks a Senior Quantitative Analytics Specialist to design, develop, and deploy financial models using state-of-the-art techniques. The role involves partnering with line of business executives and senior leaders to frame problems and define business objectives. The successful candidate will have a strong understanding of financial regulatory requirements and corporate model risk policy.

What You Will Do

The Senior Quantitative Analytics Specialist will design and build effective data visualizations, communicate results to the line of business, and write comprehensive and accurate finance model development documentation. They will also contribute to data science teams to stay concurrent with cutting-edge algorithms methodologies and work with technology and production teams to operationalize financial models.

Why It Might Be a Fit

The successful candidate will have a Master's degree in Management Sciences and Quantitative Methods, Statistics, Mathematics, or a related quantitative discipline, plus 4 years of experience in the job offered or in a related quantitative analytics role. They will have strong skills in data transformation, model development, and machine learning techniques, as well as experience with big data tools and cloud platforms.

Requirements

• Master’s degree in Management Sciences and Quantitative Methods, Statistics, Mathematics, or related quantitative discipline
• 4 years of experience in the job offered or in a related quantitative analytics role
• Data transformation and data wrangling experience using tools such as SQL
• Experience with model development using statistical modeling and machine learning techniques
• Proficiency in programming languages Python, Java, Scala, or R
• Solid understanding of machine learning techniques including neural networks, RandomForest, GBM and SVM
• Solid understanding of statistical modeling techniques including time series forecasting, linear regression, logistic regression, panel data analysis
• Experience with big data tools Spark, Hive, Kafka, and Map Reduce
• Experience with machine learning libraries MLlib, scikit-learn, H2O
• Experience with cloud platforms GCP, AWS, and Azure

Benefits

• Health benefits
• 401(k) Plan
• Paid time off
• Disability benefits
• Life insurance, critical illness insurance, and accident insurance
• Parental leave
• Critical caregiving leave
• Discounts and savings
• Commuter benefits
• Tuition reimbursement
• Scholarships for dependent children
• Adoption reimbursement