In this role, you will:
- Quantitative Analytics Specialist/Data Scientist is a partner-facing role and is responsible for delivering high impact analytics, and data science projects by using analytics, Machine Learning and Artificial Intelligence (ML/AI) with a focus on Digital, Information Security, Cyber Security, and Technology.
- Primary role of the incumbent in the AI Model Development COE is to apply business knowledge and advanced programming skills, and ML/AI to serve as a subject matter expert, analyst, hands-on practitioner to support model lifecycle – data analysis, model development, performance metrics, model implementation, model production, delivery of model results, change management, documentation and governance.
- Maintains deep understanding of information security tools and technologies, emerging security issues, risks, vulnerabilities and guides others in implementing AI/ML solutions.
- Designs, develops and implements advanced cyber security solutions, leads and influence teams and stakeholders to address security concerns / issues during the planning lifecycle; develop solutions that address multiple classes of security challenges
- Lead cross-functional initiatives including creation, implementation, documentation, validation, articulation and defense, of highly advanced model development work
- Strategize short and long-term objectives, and provide analytical support for a wide array of business initiatives
- Applies the theory and mathematics behind the analysis and modeling
- Review and assess models inclusive of technical, audit, and market perspectives
- Collaborate and consult with stakeholders including regulators and auditors
- Present strategies and results of analysis and insights
Required Qualifications:
- 5+ years of Quantitative Analytics experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
- B.Tech/B.Engg/M.Tech/M.Engg/Ph.Dor equivalent in a quantitative field such as Applied Mathematics, Statistics, Physics, Economics, Computer Science,Information technology, Electrical Engineering, Electronics and Telecommunication Engineering
- Demonstrated experience at leading and delivering multiple modeling and advanced analytics projects in an end-to-end manner in the last 5 years
- Expertise in SQL, Python programming, Spark/PySpark, Github, Splunk, H20 and strong experience with AI/ML 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
- Experience in implementing machine learning algorithms such as, decision trees and bagging/ boosting ensembles, isolation forests, model stacking, logistic regression, clustering, neural networks etc.
Desired Qualifications:
- Excellent verbal, written, and interpersonal communication skills.
- Strong analytical skills with high attention to detail and accuracy.
- Knowledge and experience in Banking or Finance domain
- Experience with UNIX/LINUX environments, and understanding of app security, cloud security, security operations
- Understanding of Deep-learning and Gen AI
Job Expectations:
30 Aug 2024
Wells Fargo Recruitment and Hiring Requirements:
b. Wells Fargo requires you to directly represent your own experiences during the recruiting and hiring process.