SAS modelers for loss forecasting team.
Experience with financial services and predictive analytics is a must.
Experience with regulatory capital calculations preferred (Basel, CCAR, CECL ‘type’ of work).
SAS modeler job often needs skills around R / Python, Statistical modelling, RapidMIner, Weka, Matlab, etc.
The Senior Analyst will be a member of the Model Implementation team for a top international commercial bank.
This individual must also be comfortable explaining and defending results and analyses to senior leadership.
This person will be able to successfully contribute to large projects that include highly complex, data intensive problems that require the coordination of resources from many different areas of the Bank.
This person should also demonstrate ownership over assigned tasks and be able to contribute to a team of highly sophisticated risk professionals.
This is a unique opportunity to work at an Advanced IRB accredited institution in driving industry-leading practices.
- Perform robust and accurate implementation of model methodologies on SAS and Python platforms
- Keep abreast of relevant development streams in preparation for implementation
- Become a subject matter expert in relevant models, source data, data query and programming techniques
- Enhance econometric and statistical understanding via projects and self-training
- Continually improve SAS and Python programming skills
- Utilize advanced statistical, financial, and economic concepts to develop risk-based analysis and implementations that can be used by management in business decisions, such as risk management and capital allocation, to ensure business value is being delivered.
- Contribute to the overall development and implementation of technical advances in risk-based methodology to meet business needs.
- Analyze and document results for a wide range of internal and external audiences, including senior management and bank regulators. Report on the results consistent with regulatory expectations.
- Act as an expert resource for the business in the fields of programming, bank data and querying, and risk quantification, working closely with your team and other stakeholders, both internal and external to the bank.
- Collaborate with a team of analytical professionals, ensuring organizational priorities are achieved on time and without error.
- Bachelors or Master’s degree in a quantitative field: Economics, Finance, Statistics, Physics, or a related discipline. Master’s degree preferred.
- 1-3 years of relevant experience or demonstrated required level of proficiency
- Experience in statistical modeling and data analysis, including knowledge of SAS or other statistical software. Prior banking or financial services experience preferred.
- Knowledge of Risk Management Policies, Regulations, Processes and Procedures:
- Monitors adherence to policies, regulations, processes and procedures within function and actively undertakes corrective action where necessary
- Understands end to end processes across the Bank and how processes are integrated
- Has a practical knowledge of regulations impacting area supported
- Continuous Process Improvement:
- Designs, develops and drives the adoption of risk management policies, processes, and procedures
- Applies advanced skills in operational processes and uses it to improve work efficiency and quality
- Data Analytics:
- Designs analysis (data and methodology) in innovative ways to identify the root cause of issues
- Adapts technical communications to different audience/ business needs to facilitate decision making
- Uses knowledge, experience, and intuition to both identify root cuase and recommends alternative solutions