Quantitative Finance Analyst

2 weeks ago


Jersey City, United States Bank of America Full time

Quantitative Finance Analyst - Enterprise Risk Analytics (ERA) page is loaded

Quantitative Finance Analyst - Enterprise Risk Analytics (ERA)

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locations

Jersey City

Atlanta

Chicago

Charlotte

time type

Full time

posted on

Posted Yesterday

job requisition id

24013839

Job Description: At Bank of America, we are guided by a common purpose to help make financial lives better through the power of every connection. Responsible Growth is how we run our company and how we deliver for our clients, teammates, communities and shareholders every day. One of the keys to driving Responsible Growth is being a great place to work for our teammates around the world. We’re devoted to being a diverse and inclusive workplace for everyone. We hire individuals with a broad range of backgrounds and experiences and invest heavily in our teammates and their families by offering competitive benefits to support their physical, emotional, and financial well-being. Bank of America believes both in the importance of working together and offering flexibility to our employees. We use a multi-faceted approach for flexibility, depending on the various roles in our organization. Working at Bank of America will give you a great career with opportunities to learn, grow and make an impact, along with the power to make a difference. Join us Job Description: This job is responsible for conducting quantitative analytics and modeling projects for specific business units or risk types. Key responsibilities include developing new models, analytic processes, or systems approaches, creating technical documentation for related activities, and working with Technology staff in the design of systems to run models developed. Job expectations include having a broad knowledge of financial markets and products. Responsibilities: Performs end-to-end market risk stress testing including scenario design, scenario implementation, results consolidation, internal and external reporting, and analyzes stress scenario results to better understand key drivers Supports the planning related to setting quantitative work priorities in line with the bank’s overall strategy and prioritization Identifies continuous improvements through reviews of approval decisions on relevant model development or model validation tasks, critical feedback on technical documentation, and effective challenges on model

development/validation Supports model development and model risk management in respective focus areas to support business requirements and the enterprise's risk appetite Supports the methodological, analytical, and technical guidance to effectively challenge and influence the strategic direction and tactical approaches of

development/validation

projects and identify areas of potential risk Works closely with model stakeholders and senior management with regard to communication of submission and validation outcomes Performs statistical analysis on large datasets and interprets results using both qualitative and quantitative approaches Skills: Critical Thinking Quantitative Development Risk Analytics Risk Modeling Technical Documentation Adaptability Collaboration Problem Solving Risk Management Test Engineering Data Modeling Data and Trend Analysis Process Performance Measurement Research Written Communications Minimum Education Requirement:

Graduate degree in quantitative or STEM discipline (e.g. Mathematics, Economics, Engineering, Finance, Physics) Overview of the Role The candidate will have the opportunity to learn the models, software development and technology infrastructure for multiple areas in Enterprise Risk Analytics (ERA) like Scenario Generation, Financial Crimes, Financed Emissions and Operational Risk, interact with industry-leading subject matter experts, apply software engineering skills and development skills to meet business and regulatory requirements, and develop a career in this fast-paced and ever-changing world. This role demands a highly technical skillset, including analytical, programming, organizational, communication, and software design capabilities. This role will build software in Python or PySpark for technology integration and use

Hadoop/HIVE/Oracle/Exadata

for model data input and output Position Overview Responsible for model implementation using software standards and controls on models developed by model development team, develop model execution code including GRA Core Platform (GCP) workflows and develop operational functionalities to support the models in production. Participate in Python implementation of new and existing models, analytic processes or system approaches. Participate in building out strategic model development infrastructure using Python and PySpark. Create technical documentation and work with technology teams in deployment of the code in production. Incumbents possess good quantitative and Python programming skills and able to understand and contribute to meeting software design standards and GRA code controls standards Required Education, Skills, and Experience Graduate degree in quantitative or STEM discipline (e.g. Mathematics, Economics, Engineering, Finance, Physics) 5+ years’ experience in programming in Python 3-5 years’ experience in programming in any of the databases like Oracle/Hadoop/HIVE 2-3 years’ experience in developing with JIRA and Git Experience in writing functional specs for software implementation Good analytical and problem-solving skills Basic Software engineering and design skills and focus on using good software development practices Strategic thinker with aptitude to use technical skills to solve business problems Desired Skills and Experience Experience designing, developing, and applying scalable infrastructure solutions PySpark development experience Able to document process steps, inputs, outputs, requirements, identify gaps and improve workflow Shift: 1st shift (United States of America)

Hours Per Week: 40

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Considerations when writing a resume • Do be brief. Resumes should be 1-2 pages in length. • Do be upbeat and active in your wording. • Do emphasize what you have done clearly and concretely. • Do be neat and well organized. • Do have others proofread and critique your resume. Spell check. Make it error free. • Do use high quality, white or light colored 8½ x 11 paper. Use a laser printer if possible. • Don't be dishonest, always tell the truth about yourself in the most flattering light. • Don't include salary history or requirements. • Don't include references. • Don't include accomplishments that do not support your professional goals. •

Don't include anything that isn't relevant. (For example, don't mention your fondness for swimming unless you want to work on the water.) • Don't use italics, underlining, shadows or other fancy treatments. Seven steps to a successful interview 1. Anticipate –Put yourself in the interviewer's position. What do you believe the interviewer is most interested in? Why do you think you have been invited to interview? 2. Research –What are the primary functions of the line of business? What are the success factors for the job? Is there a job description available? 3. Assess –Think about your skills, abilities, knowledge, interests, traits, values and accomplishments. Match them to what you know about the job. Consider which ones you should highlight. 4. Prepare Answers –Think about what the interviewer may ask, determine what the best answer is and write it down. 5. Prepare Questions – Interviewing is a two-way street. By asking thoughtful questions, you communicate your interest and learn a lot about the job. Choose two or three questions to ask your interviewer. Avoid asking a lot of questions about vacation time or breaks. 6. Practice – It may seem awkward, but it is the best way to come across well in an interview. Practice your own "great responses" with others or in front of a mirror until you appear relaxed and at ease. 7. Follow-up – Send a brief follow-up letter to the interviewer. Keep in mind that the many job searchers will not send a follow-up letter. Sending one can become a competitive advantage.

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