Job Highlights
Title | Manager (Liquidity Research/Analytics) |
Type | Full Time |
Experience | 5-7 Years |
Function | Finance/Accounting |
Location | Chicago, IL, United States |
Company | BMO (USA) |
Company Profile
BMO is a leading North American bank and provides personal and commercial banking, global markets, and investment banking services.
Job Profile
The bank is seeking a Manager (Liquidity Research/Analytics) who will play a key role in the development of quantitative methodologies to inform behavioral assumptions for use in the Internal Liquidity Stress Test which is a critical tool for senior leaders to manage the bank’s liquidity risk.
Be proficient in handling large volumes of data using a programming language such as SQL, SAS, R, and Python and using critical thinking and problem-solving skills to develop an in-depth understanding of BMO’s products and customers to inform liquidity risk management.
Be responsible for creating visualizations for dissemination of their analyses using tools such as Power-BI.
Education Level
- Post-secondary Degree in a Quantitative Discipline such as Financial Engineering, Data Science, Statistics, Economics, Natural Sciences, or other related field of study or an equivalent combination of education and experience.
Work Experience
- Typically, between 5-7 years of relevant experience
Duties/Responsibilities
- Applies scripting/programming skills to assemble various types of source data (unstructured, semi-structured, and structured) into well-prepared datasets with multiple levels of granularities (e.g., demographics, customers, products, transactions).
- Broader work or accountabilities may be assigned as needed.
- Builds effective relationships with internal/external stakeholders and ensures alignment.
- Develops agreed analytical solution by applying suitable statistical & machine learning techniques (e.g., A/B testing, prototype solutions, mathematical models, algorithms, machine learning, deep learning, artificial intelligence) to test, verify, and refine hypotheses.
- Develops analytical solutions and makes recommendations based on an understanding of the business strategy and stakeholder needs.
- Documents data flow, systems, and processes in data collection to improve efficiency and apply use cases.
- Exercises judgment to identify, diagnose, and solve problems within given rules.
- Focus is primarily on business/group within BMO; may have broader, enterprise-wide focus.
- Leads/participates in the design, implementation, and management of core business/group processes.
- Performs experimental design approaches to validate findings or test hypotheses.
- Provides advice and guidance to assigned business/group on the implementation of analytical solutions.
- Summarizes statistical findings and concludes, and presents actionable business recommendations. Presents findings and recommendations in a simple, clear way to drive action.
- Supports the development and execution of strategic initiatives in collaboration with internal and external stakeholders.
- Supports the development of tools and delivers training for data analytics and AI.
- Uses the appropriate algorithms to discover patterns.
- Works independently on a range of complex tasks, which may include unique situations.
- Works with stakeholders to identify the business requirements, understand distinct problems and expected outcomes, and models and frame business scenarios that impact critical business processes or decisions.
- Works with various data owners to discover and select available data from internal sources and external vendors (e.g. lending system, payment system, external credit rating system, and alternative data) to fulfill analytical needs.
Skills/Knowledge/Abilities
- Analytical and problem-solving skills (in-depth)
- Collaboration and team skills (in-depth)
- Data-driven, and decision-making (in-depth)
- Experience in statistical analysis, data mining, and data cleansing/transformation.
- Experience with distributed computing language (e.g. Hive/Hadoop/Spark) and cloud technologies (e.g. AWS Sagemaker, AzureML).
- Experience with programming languages (e.g. SQL, Python, R, SAS, SPSS, Perl) and machine learning/deep learning algorithms/packages (e.g. XGBoost, H2O, SparkML).
- Influence skills (in-depth)
- Knowledge of distributed computing or distributed databases.
- Knowledge of visualization techniques and concepts.
- Technical proficiency gained through education or business experience.
- Verbal and written communication skills (in-depth)
Benefits/Perks
- The bank offers health insurance, tuition reimbursement, accident and life insurance, and retirement savings plans.
Employer’s Statement
BMO is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law.
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