Wells Fargo
Senior Data Science ConsultantPosted
2 weeks 3 days ago
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Job Description
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Why Wells Fargo:
This is where your true career begins. We ranked #2 on the 2023 LinkedIn Top Companies list - and #1 among financial services companies - as the best workplace "to grow your career" in the U.S. At Wells Fargo, we support employees' career aspirations and growth. We're proud of our employee-welfare-centered business approach and our commitment to diversity, equity, and inclusion in the workplace.
We offer competitive salaries and one of the richest benefits packages in the industry. Our Total Rewards program focuses on wellness, work-life balance and the financial health of our employees. Our customers invest with us, we invest in you. Apply today.
About this role:
Wells Fargo is seeking a Senior Data Science Consultant within the Enterprise Complaints Remediations (ECR) organization.
In this role, you will:
* Lead or participate in moderately complex initiatives and deliverables by utilizing data-driven, advanced analytical, statistical techniques, algorithms, or models to make actionable insights, trends, recommendations, or contribute to large-scale planning that has a broader impact
* Review and analyze moderately complex, large structured and unstructured data sets from various sources, requiring an in-depth hypothesis generation and advanced analysis of variable factors to convert data into meaningful insights and recommendations
* Independently analyze and resolve moderately complex issues and lead team to meet deliverables while leveraging solid understanding of analytic capabilities
* Collaborate and consult with peers, colleagues, and mid-level managers to drive recommendations and strategies based on data-driven analytical insights, trends, and patterns that will resolve issues and achieve goals; may lead projects, teams, or serve as a mentor for lower-level staff
* Execute analytical experiments and create innovative statistical models to discover solutions for abstract business problems across various domains
* Interpret and analyze data, using advanced analytics modeling methods and programming, to recommend ways to solve problems and influence business decisions and strategies
* Communicate actionable insights and recommendations using data in a digestible format to a non-technical audience of varying levels
Required Qualifications:
* 4+ years of data science 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:
* 4+ years of experience with Python
* 3+ years of experience with SAS, Teradata, PySpark, SQL, and Machine Learning (ML) and Natural Language Processing (NLP) & Large Language Model (LLM) experience.
* 2+ years of experience with model development and model validation experience.
* Ability to leads or assist on end-to-end model build efforts from discovery to deployment.
* Experience working with technology partners and model governance.
* Communicates project progress and obstacles.
* Excellent communication skills and ability to articulate complex material to a diverse audience.
* Performs pre-/post-model testing, including explain-ability, robustness, fairness testing, etc.
* Shepherds model from discover to deployment including post-validation activities.
* Documents model development in MDD.
* Conducts ongoing monitoring and reviews.
Posting End Date:
25 Aug 2024
* Job posting may come down early due to volume of applicants.
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, national origin, disability, status as a protected veteran, or any other legally protected characteristic.
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.
Applicants with Disabilities
To request a medical accommodation during the application or interview process, visit Disability Inclusion at Wells Fargo.
Drug and Alcohol Policy
Wells 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.
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