Senior Quantitative Analytics Specialists Job
- Consultancy
- 4 to 8 Yrs
- Other Karnataka
- 4 days ago
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Job Description
- About This Role Wells Fargo is seeking a Senior Quantitative analytics specialist for its Model Risk Management team. 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: 4+ years of experience with minimum Masters/Phd 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. Strong mathematical, statistical, analytical and computational skills. Strong communication skills for a variety of audiences (other technical staff, senior management and regulators) both verbally and in writing. Capability to multi-task and finish work within strict timelines and provide timely requests for information and follow-up questions. Ability to work independently on complex model validations from start to finish. Skill in managing relationships with key model stakeholders Eagerness to contribute collaboratively on projects and discussions Perpetual interest in learning something new, but being comfortable with not knowing the all the answers Attention to detail in both analytics and documentation Aptitude for synthesizing data to "form a story" and align information to contrast/compare to industry perspective Intellectually curious, who enjoy solving problems. Job Expectations: Hands on industry experience in building large scale end-to-end machine learning systems using a combination of big data tools and programming languages like Scala, Java and/or Python Knowledge of parallel and distributed computing frameworks such as Hadoop, Spark, MPI, using GPUs Experience in machine learning areas such as recommender systems, NLP, pattern recognition, predictive modeling, Artificial Intelligence. Experience implementing machine learning algorithms such as support vector machines, decision trees, logistic regression, clustering, neural networks, graphical models etc Data exploration and preparation using SAS, Spark, Python ,SQL or R or any statistical tool Working experience in financial model validation team would be added advantage Prepare detailed documentations for projects for both internal and external that complies regulatory and internal audit requirements Keep updated with the latest in the Data Science community and leverage new capability for the bank Knowledge of banking industry, terminologies and products in at least one of the LOB such as credit cards, mortgage, deposits, loans or wealth management etc. Knowledge of any functional area such as risk, marketing, operations or supply chain in banking industry. Instrumental in bringing new approaches to the table, create white papers and present in conferences Posting End Date: 23 Mar 2025 Job posting may come down early due to volume of applicants. We Value Diversity 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 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 Third-Party recordings are prohibited unless authorized by Wells Fargo. Wells Fargo requires you to directly represent your own experiences during the recruiting and hiring process. Reference Number R-443462,
Employement Category:
Employement Type: Full timeIndustry: BFSI
Role Category: Not Specified
Functional Area: Not Specified
Role/Responsibilies: Senior Quantitative Analytics Specialists Job
Contact Details:
Company: Wells FargoLocation(s): Other Karnataka
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Keyskills: Quantitative Analytics Market Risk Management Credit Risk Management Operational Risk Management Model Validation Machine Learning Java Python Spark MPI Recommender Systems Pattern Recognition Predictive Modeling Artificial Intelligence Data Preparation SAS SQL R Programming Regulatory Compliance Risk Management Marketing Operations Management Supply Chain Management
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