About this role:
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
Required Qualifications:
- 4+ 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 discipline such as mathematics, statistics, engineering, physics, economics, or computer science
Desired Qualifications:
- BS/BA degree or higher 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
- Experience with NLP (Natural language processing), Large Language models (LLM), BERT, Llama, Gemini- pro, vertex AI
- Experience with supervise , unsupervised & semi supervise learning
- Experience with Deep-learning, Artificial intelligence techniques, Generative AI and Prompt engineering solutions.
- Strong programing skill
- Expertise in analytic tools : R, Python, Scala, Java
- Big Data skills – Aster, Hadoop, SPARK, H20 and various big data distributions like Hortonworks and MapR
- NLP, Text mining, Image/Voice processing, digital analytics, deep learning, machine learning
- Strong collaboration skills
- Output deployment using appropriate technologies (HTML5, Shiny, Django)
- Working expertise in Tensorflow, Keras or Pytorch would be added advantage
- Ability to translate analytical data into useful business information
- 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.
- Knowledge of functional area such as risk, marketing, operations or supply chain in banking industry.
- Ability to multi-task and prioritize between projects
- Ability to work independently and as part of a team
- Data Engineering
- Sql ,Teradata, Hadoop, Spark
- Exploratory Data analysis
- Provide exploratory data analysis using Python/R/SAS / SQL
- Experience with Databases like oracle , Teradata, Sql server
- Advance Excel skills
- Data integration and clean up data for the usage
- Experience with structured data and semi-structured text or Excel files
- Business Intelligence
- Tableau, Power BI, Shiny, Dash, HTML5
- Business Analytics
- Data mining and Insights
- Trend Analysis, forecasting and pattern recognition
- Find opportunities in the data and able to communicate to the partners
- Consult with partners to define issues/information needs.
- Present findings to multiple levels of management
- Ensure that analyses are delivered on time, while surpassing partner expectations
- Ensure partner transparency throughout the life of the project
- Proactively seek opportunities to increase the value of analysis
- Strong oral and written communication and consultative skills
Job Expectations
- Person would be required to work individually or as part of a team on data science projects and work closely with business partners across the organization.
- He/She would perform Data wrangling activities.
- He/she 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.
- Work closely with data engineers, BI and UI specialists and deliver top notch analytical solution for the bank.
- Define business problem and translate it into analytical problem.
18 Feb 2025
Wells Fargo Recruitment and Hiring Requirements:
b. Wells Fargo requires you to directly represent your own experiences during the recruiting and hiring process.