Senior Lead Data Science Consultant
110378-IND-CHENNAI-INTL CHN EMBASSY SPLENDID BLK 9, India
Wells Fargo
Committed to the financial health of our customers and communities. Explore bank accounts, loans, mortgages, investing, credit cards & banking services»About this role:
Wells Fargo is seeking a Senior Lead Data Science Consultant...
Position requires a Bachelors / Master’s degree in Mathematics, Statistics, or related quantitative field and four 10+ years of experience in the job offered or in a related quantitative analytics role.
Specific skills required:
- Quantitative experience with credit risk, loss forecasting or stress testing methodologies;
- Experience validating macro-economic scenario forecasts;
- Experience with the development and oversight of methodologies used in commercial modeling, investment securities, and economic modeling;
- Strong quantitative skills with a background in mathematical and/or statistical techniques used in stress test modeling such as logistic regression, Monte Carlo simulation, time series modeling, machine learning, and hazard modeling;
- Programming skills with strong experience in model development and performance testing methodology using SAS, Python, R, or other statistical software;
- Business acumen with the ability to engage diverse stakeholders for the planning and completing of complex model validation projects independently and effectively; and
- Develop best-in-class transactional and application risk models leveraging cutting-edge advanced AI/ML techniques
- Lead and participate in critical debugging, testing and performance tuning for machine learning and/or statistical models written in python code
- Conduct ad-hoc analysis and reporting as required
- Responsible for documenting and presenting detailed model development processes and results, suitable for a variety of audiences
- Lead and participate intensive team discussions, interactions with cross-functional teams, and dialogues with internal reviewers (Model Validation and Internal Audit)
- Collaborate with key business model users to ensure models are business driven, properly implemented and executed
- Respond to ongoing analytical requests from auditors and regulatory reviewers in timely manner
- Essential Skills:
- 10+ years of analytics experience with experience in customer call analytics and escalated complaints analytics.
- Master's degree or higher in a quantitative field such as mathematics, statistics, engineering, physics, economics, or computer science
- 10+ years of programming experience in SAS, Python, Tableau & ThoughtSpot.
- Experience in LLM/Topic Modelling & ML model development and/or monitoring
- Excellent verbal and written communication skills
- Experience in producing high quality technical documentation with tools such as Excel, Word, PowerPoint
Desired Skills:
- Bachelors/Masters in Analytics or similar quantitative disciplines
- Experience in statistical modeling techniques
- Exposure to machine learning techniques (Random Forest, XG Boost, Light GBM, Neural Networks, LLM and so on)
- Developed Fraud Risk Model using Python or other vendor based tools
- Excellent problem solving skills and ability to connect dots, see big picture and find solutions and articulate in a clear manner.
- Understanding of process, methodologies used in credit/fraud scoring model development, implementation, validation and monitoring
- Ability to effectively manage multiple assignments with challenging timelines
Posting End Date:
3 Apr 2025*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.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Computer Science Credit risk Economics Engineering Excel Fraud risk LLMs Machine Learning Mathematics ML models Monte Carlo Physics Python R SAS Statistical modeling Statistics Tableau Testing
Perks/benefits: Career development
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