About Wells Fargo
Wells Fargo & Company (NYSE: WFC) is a leading global financial services company headquartered in San Francisco (United States). Wells Fargo has offices in over 20 countries and territories. Our business outside of the U.S. mostly focuses on providing banking services for large corporate, government and financial institution clients. We have worldwide expertise and services to help our customers improve earnings, manage risk, and develop opportunities in the global marketplace. Our global reach offers many opportunities for you to develop a career with Wells Fargo. Join our diverse and inclusive team where you will feel valued and inspired to contribute your unique skills and experience. We are looking for talented people who will put our customers at the center of everything we do. Help us build a better Wells Fargo. It all begins with outstanding talent. It all begins with you.
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About this role:
Wells Fargo is seeking Lead Quantitative Model Solutions Specialist
In this role, you will:
Lead complex, large-scale model maintenance, optimization, and planning initiatives related to operational processes, controls, reporting, testing, implementation, and documentation
Review and analyze complex multi-faceted model operations and optimization challenges that require in-depth evaluation of multiple factors including intangibles or unprecedented factors
Develop model processes and optimization strategies for short- and long-term objectives; support and provide insights regarding a wide array of business initiatives
Make decisions in complex and multi-faceted situations requiring solid understanding of agile development
Influence global assessment of model maintenance schedules inclusive of engineering, structure, and scope of review following the System Development Life Cycle process, quality, security, and compliance requirements
Strategically collaborate and consult with peers, colleagues, and managers to resolve issues and achieve goals
Required Qualifications:
5+ years of quantitative model solutions or quantitative model operations experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
Required Qualifications:
- 5+ years of quantitative model solutions or quantitative model operations experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
- Required to work individually or as part of a team on multiple data science projects and work closely with business partners across the organization. Mentor and coach budding Data Scientist on developing and implementing data science solutions.
- Perform various complex activities related to statistical/machine learning. Provide analytical support for developing, evaluating, implementing, monitoring and executing models across business verticals using emerging technologies including but not limited to Python, Spark, and H2O etc.
- Expert knowledge on working on large datasets using SQL and present conclusions to key stakeholders.
- Establish a consistent and collaborative framework with the business and act as a primary point of contact in delivering the solutions.
- Experience in building quick prototypes to check feasibility and value to business.
- Expert in developing and maintaining modular code-base for reusability
- Review and validate models and help improve the performance of the model under the preview of the banking regulations.
- Work closely with multiple teams such as technology, ML Ops, MRM teams to deploy the models to production.
- Prepare detailed documentations for projects for both internal and external that complies regulatory and internal audit requirements
- Mentor and guide junior team members and work on multiple analytics/data science initiatives.
- M.Sc./M.Phil. in statistics/ economics/ mathematics/ operations research engineering physics
- 3+ years of must have hands on exposure in Python, PySpark and SQL.
- Expert knowledge of libraries like sckit-learn, pandas, numpy, mllib, matplotlib, keras...
- Expert in data mining and statistical analysis.
- 5+ Experience in developing, implementing models.
- Statistical models - linear regression, logistic regression, time series analysis, multivariate statistical analysis
- Machine learning models - Random Forest, XGBoost, GBM, SVM
- Exposure to deep learning framework - ANN,RNN, CNN, LSTM
- Excellent understanding of model metrics including AUC, ROC, F-statistics etc. with clear understanding of how model performance is tuned
- Strong programing skills.
- Hands on knowledge in one or more of Big Data skills - SQL, Aster, Teradata, Hadoop, SPARK, H20, Big Query.
- Exposure to Google Cloud Platform
- Critical thinking and strong problem solving skills
- Ability to learn the business aspects quickly and handle multiple projects.
- 2+ years of knowledge of banking industry and products in at least one of the LOB such as credit cards, mortgage, deposits, loans or wealth management etc.is desirable
- Knowledge of functional area such as risk, marketing, operations or supply chain in banking industry is desirable
- Ability to multi-task and prioritize between projects
- Ability to work independently and as part of a team
- Working expertise in Tensorflow, Keras or Pytorch would be added advantage.
- Working knowledge in developing end to end ML/AI pipeline in Apache Spark, Sparkling Waters, H2O, Caffe in Hortonworks/Cloudera a/MapR or Teradata Aster big data platforms.
- Ability to work with Data Engineers in discovering and optimizing bottlenecks in the AI/ML pipeline for real-time or near-real-time applications that consumes large throughput of data
*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.