About this role:

Wells Fargo is seeking a Senior Quantitative Analytics Specialist.

In this role, you will:

• Perform highly complex activities related to creation, implementation, and documentation
• Use highly complex statistical theory to quantify, analyze and manage markets
• Forecast losses and compute capital requirements providing insights, regarding a wide array of business initiatives
• Utilize structured securities and provide expertise on theory and mathematics behind the data
• Manage market, credit, and operational risks to forecast losses and compute capital requirements
• Participate in the discussion related to analytical strategies, modeling and forecasting methods
• Identify structure to influence global assessments, inclusive of technical, audit and market perspectives
• Collaborate and consult with regulators, auditors and individuals that are technically oriented and have excellent communication skills
• Senior Quantitative Analytics Specialists an individual contributor role in the Decision Science and Artificial Intelligence (DSAI) Validation team within CMoR. In this role, the team member is responsible for validating and approving all marketing, retail credit scoring, commercial credit scoring, financial crimes, fair lending, and other artificial intelligence and machine-learning models.
• A Senior Quantitative Analytics Specialist should have a deep academic knowledge, broad based approach to solutioning business problems. He/she should approach the problem agnostic of analytic technique, tool or process. Ability to think outside the box and provide ensemble solutions should set them apart to be a high performing team member.

• 4+ years of Quantitative Analytics experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
• 4+ years of experience with minimum Masters/Phd in a quantitative field such as applied math, statistics, engineering, physics, accounting, finance, economics, econometrics, computer sciences, or business/social and behavioral sciences with a quantitative emphasis.
• Strong mathematical, statistical, analytical and computational skills.
• Strong communication skills for a variety of audiences (other technical staff, senior management and regulators) both verbally and in writing.
• Capability to multi-task and finish work within strict timelines and provide timely requests for information and follow-up questions.
• Ability to work independently on complex model validations from start to finish.
• Skill in managing relationships with key model stakeholders
• Eagerness to contribute collaboratively on projects and discussions
• Perpetual interest in learning something new, but being comfortable with not knowing the all the answers
• Attention to detail in both analytics and documentation
• Aptitude for synthesizing data to 'form a story' and align information to contrast/compare to industry perspective
• Intellectually curious, who enjoy solving problems.

• Hands on industry experience in building large scale end-to-end machine learning systems using a combination of big data tools and programming languages like Scala, Java and/or Python
• Knowledge of parallel and distributed computing frameworks such as Hadoop, Spark, MPI, using GPUs
• Experience in machine learning areas such as recommender systems, NLP, pattern recognition, predictive modeling, Artificial Intelligence.
• Experience implementing machine learning algorithms such as support vector machines, decision trees, logistic regression, clustering, neural networks, graphical models etc
• Data exploration and preparation using SAS, Spark, Python ,SQL or R or any statistical tool
• Working experience in financial model validation team would be added advantage
• Prepare detailed documentations for projects for both internal and external that complies regulatory and internal audit requirements
• Keep updated with the latest in the Data Science community and leverage new capability for the bank
• Knowledge of banking industry, terminologies and products in at least one of the LOB such as credit cards, mortgage, deposits, loans or wealth management etc.
• Knowledge of any functional area such as risk, marketing, operations or supply chain in banking industry.
• Instrumental in bringing new approaches to the table, create white papers and present in conferences