About this role:Wells Fargo is seeking 2 Lead Data Scientists to join our Corporate and Investment Banking (CIB) Data Management Team to help tackle our toughest and most exciting data science challenges across multiple divisions of CIB.
This is a unique and innovative opportunity to leverage strong analytical skills and expertise in Machine Learning, NLP, and GenAI to extract insights from complex datasets and drive data-driven decision-making across Wells Fargo CIB business units. The ideal candidate will engage business stakeholders at the most senior level and collaborate with cross-functional teams to build and deploy descriptive, predictive, and generative capabilities to uncover actionable business insights.
The role is hybrid role with some on office expectation. Learn more about our career areas and business divisions at wellsfargojobs.com.
In this role you will:- Collaborate with CIB stakeholders to develop an understanding of needs from data science perspective
- Identify relevant data sources, then perform data cleaning and analysis of large data sets needed by the AI/GenAI/ML Models
- Carry out the preprocessing of structured and unstructured data to be used for analysis
- Identify and recommend analysis of data quality or integrity issues
- Perform feature engineering, extracting signals needed by the Models
- Collaborate with the Data Science team to build AI/GenAI/ML Models
- Present results in a clear manner to diverse audiences
- Propose solutions and strategies to tackle data science challenges
Required Qualifications:- 5+ years of Data Management, Business Analysis, Analytics, or Project Management experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
Desired Qualifications:- Master's degree in Computer Science, Mathematics, Statistics, Physics, Engineering or other relevant technical Fields
- Minimum 5+ years of industry experience in developing Machine Learning and Statistical Models from idea generation to objective formulation to implementation and deliverables with application to Investment Banking
- Proven industry experience in natural language processing and text mining
- Strong understanding of statistical analysis, hypothesis testing, and experimental design
- Proficient in programming languages commonly used in data science (Python, R, Spark, etc.)
- Strong SQL experience
- Strong problem solving and decision-making skills with attention to detail and accuracy
- Ability to effectively form stories through data analysis
- Ability to work effectively in a team environment and across all organizational levels, where flexibility, collaboration, and adaptability are important
- Excellent verbal, written, and interpersonal communication skills
- Ability to manage multiple projects simultaneously
- Working experience with Visualization tools using PowerBI and/or Tableau
- Expertise in developing and deploying distributed ML Models on a cloud environment
- Experience in GenAI/LLM
Posting Location: New York, NY: 30 Hudson Yards
Pay Range: New York, NY: $133,300 - $237,100
Pay RangeReflected is the base pay range offered for this position. Pay may vary depending on factors including but not limited to achievements, skills, experience, or work location. The range listed is just one component of the compensation package offered to candidates.
$133,300.00 - $237,100.00
Benefits Wells Fargo provides eligible employees with a comprehensive set of benefits, many of which are listed below. Visit Benefits - Wells Fargo Jobs for an overview of the following benefit plans and programs offered to employees.
- 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
Posting End Date:24 Nov 2024
* Job posting may come down early due to volume of applicants. We Value DiversityAt 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, national origin, disability, status as a protected veteran, or any other legally protected characteristic.
Applicants with DisabilitiesTo request a medical accommodation during the application or interview process, visit Disability Inclusion at Wells Fargo .
Drug and Alcohol PolicyWells Fargo maintains a drug free workplace. Please see our Drug and Alcohol Policy to learn more.
Wells Fargo Recruitment and Hiring Requirements:a. Third-Party recordings are prohibited unless authorized by Wells Fargo.
b. Wells Fargo requires you to directly represent your own experiences during the recruiting and hiring process.
