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Business Intelligence Analyst
1 month ago
Responsibilities:
- Partner with business leaders across the organization to define business problems and research questions; serves as key resource and Subject Matter Expert (SME) on cross functional, matrixed teams to solve highly complex work critical to the organization.
- Maintain predictive model development, implementation, and management. This includes writing the code, training/fitting of the model parameters.
- Develop models to forecast new origination growth, balance attrition and profitability by channel, including the creation of lifetime value modeling and portfolio valuations.
- Develop models to support price and fee sensitivities and hold versus sell decision parameters.
- Support treasury cashflow models for credit analytics.
- Perform independent model testing, including evaluation of mathematical soundness, developmental evidence, historical performance, statistical testing, back testing, model benchmarking and appropriate sensitivity analyses.
- Prepare and retain full documentation of the model development process, any associated testing performed, all modelling assumptions (particularly management assumptions), and relevant control and governance processes surrounding model.
- Present quantitative results clearly and concisely and display a capability to discuss statistical and quantitative concepts coherently.
- Work with cross-functional areas to develop predictive models such as renewal trends and other behavior models.
- Strong communication and interpersonal skills and ability to explain complex modeling techniques.
- Lead analytic efforts in support of the continuous improvement of profitability and acquisition channel optimization.
- Responsible for portfolio monitoring and portfolio stress testing.
- Ensure individual objectives are aligned to achieve the overall corporate goals.
Qualifications:
- Bachelor’s Degree in a quantitative field required, with preference to master’s degree in “STEM” field (Data Science, Technology, Business Intelligence, or Mathematics).
- 5+ years of experience in data analytics (minimum of 3 years); 2 years’ experience in financial services industry preferred.
- Strong proficiency in R, Python or SAS required, in addition to advanced skills in MS Office, Excel.
- In-depth understanding of SQL.
- Experienced in using multiple data science methodologies to solve complex business problems (e.g. statistical analysis, research science, machine learning and deep learning techniques, data modeling, regression modeling, financial analysis, demand modeling, etc.)
- Possess in-depth knowledge and subject matter expertise of statistical techniques and application.
- Knowledge of techniques and tools that promote analysis and the ability to effectively interpret results and determine the correct course of action.
- Technical aptitude with strong, logical, problem solving and decision-making skills.
- Strong understanding of statistical tools and their application to business, as well as principles of cost/benefit analysis, risk management, collections, and operations.
- Ability to prioritize according to the strategic direction of the organization, ability to meet deadlines and follow through on the completion of high-profile projects and initiatives.
- Highly organized and detail oriented with the proven ability to multi-task.
- Strong written and verbal communication and interpersonal skills and ability to work with various levels of an organization.