Wells Fargo | Jobs | Lead Quantitative Analytics Specialist | BigDataKB.com | 08-02-22

Wells Fargo is seeking a Lead Quantitative Analytics Specialist…

In this role, you will:

• 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

Required Qualifications, US:

• 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 field such as mathematics, statistics, engineering, physics, economics, or computer science

Required Qualifications, International:

• Experience in Quantitative Analytics, 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 field such as mathematics, statistics, engineering, physics, economics, or computer science.
• Demonstrated experience at leading and delivering multiple modeling and advanced analytics projects in an end-to-end manner.
• Expertise in Python programming and strong experience with Python packages related to modeling, data analysis, visualization and automation.
• Expertise in at least two of supervised learning, unsupervised learning, semi-supervised learning and time series analysis.
• Ability to identify and manage complex issues and negotiate solutions within a geographically dispersed organization.
• Demonstrated excellence at identifying stakeholders, understanding needs, and driving to resolution
• Strong organization skills throughout the development of analytical solutions (data analysis documentation, hypothesis documentation, code management, etc.)

Desired Qualifications:

• Excellent verbal, written, and interpersonal communication skills.
• Strong analytical skills with high attention to detail and accuracy.
• Expertise in multiple analytic tools: Python, R, SAS programming and data manipulation using SQL.
• Knowledge and experience in Banking or Finance domain.
• Experience and high degree of familiarity with advanced model development using PySpark and GitHub.
• Knowledge and experience with machine learning algorithms and time – series modeling
• Detail oriented, results driven, and has the ability to navigate in a quickly changing and high demand environment while balancing multiple priorities
• Knowledge of H2O, DataRobot, Airflow and other such automated tools.
• Knowledge ad experience in working with cloud platforms – GCP/ Azure/ AWS for model development and deployment.
• Knowledge and experience in handling large datasets using BigQuery, Hive SQL and similar languages.
• Experience with Deep-learning, Artificial intelligence techniques like ANN, CNN, DNN, RNN etc. and how to strategize deep-learning layer and activations.
• Experience implementing machine learning algorithms such as support vector machines, decision trees and bagging/ boosting ensembles, model stacking, logistic regression, clustering, neural networks, graphical models etc.
• Excellent understanding of model error and classification metrics including AUC-ROC, information retrieval metrics with clear understanding of how model performance is tuned and how models are validated
• Experience with UNIX/LINUX environments
• Experience with non-structured data problems in NLP, Text mining, Image/Voice processing, digital analytics.
• Strong familiarity with MS office – PowerPoint and Excel.

Job Expectations:

• Person would be required to lead projects alongside a Data Science Manager and also work individually or as part of a team on data science projects to liaison closely with business partners across the organization.
• Individual would be developing statistical/machine learning models using various techniques (supervised, unsupervised, semi-supervised) and technologies including but not limited to SAS, R, Python, Spark, H2O, Aster etc.
• This role would require working closely with data engineers, BI and UI specialists to deliver top notch analytical solution for the bank.
• Define business problem and translate it into analytical problem.
• Adapt at attracting, hiring and retaining top notch data science talents and build world class team
• Help create conducive environment for nurturing and growing talents.

Department Overview
EADS is the central analytics group tasked with solving high-impact business challenges and standing up cutting-edge analytical capabilities to be shared across Wells Fargo’s analytic community. We are looking for a high performer to join our team and help us solve challenging and interesting business problems through rigorous data analysis and predictive modeling. In this highly consultative and visible role, you will support development analytic projects from multiple business lines using various technology and techniques ranging from but not limited to supervised, unsupervised and semi-supervised machine learning, deep-learning, NLP, optimization algorithms.

About the Role
This is a partner-facing role and is responsible for delivering high impact analytic and data science projects across enterprise functions (DMI & COO)

We Value Diversity

At Wells Fargo, we believe in diversity, equity and inclusion in the workplace; accordingly, we welcome applications for employment from all qualified candidates, regardless of race, color, gender, national origin, religion, age, sexual orientation, gender identity, gender expression, genetic information, individuals with disabilities, pregnancy, marital status, status as a protected veteran or any other status protected by applicable law.

Employees support our focus on building strong customer relationships balanced with a strong risk mitigating and compliance-driven culture which firmly establishes those disciplines as critical to the success of our customers and company. They are accountable for execution of all applicable risk programs (Credit, Market, Financial Crimes, Operational, Regulatory Compliance), which includes effectively following and adhering to applicable Wells Fargo policies and procedures, appropriately fulfilling risk and compliance obligations, timely and effective escalation and remediation of issues, and making sound risk decisions. There is emphasis on proactive monitoring, governance, risk identification and escalation, as well as making sound risk decisions commensurate with the business unit’s risk appetite and all risk and compliance program requirements.

Candidates applying to job openings posted in US: All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, or national origin.

Candidates applying to job openings posted in Canada: Applications for employment are encouraged from all qualified candidates, including women, persons with disabilities, aboriginal peoples and visible minorities. Accommodation for applicants with disabilities is available upon request in connection with the recruitment process.