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Data-Driven Credit Risk Analytics Specialist
2 months ago
We are seeking a highly skilled Data-Driven Credit Risk Analytics Specialist to join our team at Aspire Data Recruitment. As a key member of our analytics team, you will be responsible for designing, developing, and deploying state-of-the-art, data-driven predictive models to solve business problems using the latest technologies in data mining, statistical modeling, pattern recognition, and performance inference.
Key Responsibilities- Design and Develop Predictive Models: Design and develop state-of-the-art, data-driven exploratory analysis as well as predictive and decision models to solve business problems.
- Build and Evaluate Models: Build and evaluate predictive and decision models to be deployed in production systems, or for research. This includes the analysis of large amounts of historical data, determining suitability for modelling, data clean-up, pattern identification and variable creation, selection of sampling criteria and performance definition, and variable selection.
- Experiment with Algorithms: Experiment with different types of algorithms and models, analysing performance to identify the best algorithms to employ.
- Support Technical Products: Assist with technical product support for new or existing products/services; this includes, but is not limited to, production of sales collateral or ad-hoc investigations initiated by internal or external clients. Work simultaneously on multiple projects of moderate size and complexity.
- Plan and Manage Projects: Plan effectively to set priorities and manage projects, identify roadblocks and work to get them removed, and understand the importance of meeting deadlines.
- Communicate with Clients: Handle communication with internal and external clients as needed.
- Determine Model Report Format: Determine appropriate model report format for communication with clients.
- Author White Papers and Proposals: Participate in authoring white papers, proposals and publications.
- Mentor and Assign Tasks: Mentor other scientists and assign modelling tasks when appropriate.
- A graduate, ideally with a mathematical or statistical degree (or a degree with a high level of quantitative, statistical or operational research content) or relevant experience.
- Experience with an analytic solutions or consulting company, and preferably in a client-facing project management capacity.
- Knowledge and experience in applying data to solve business problems through quantitative analysis, experience with predictive modelling and optimisation, and knowledge of the principles and practices of project management.
- Experience with credit risk model developments. Experience with fraud and marketing analytics a plus.
- Strong statistical, data processing and analytical skills.
- An excellent communicator with the ability to explain complex concepts and describe technical material to non-technical users.
- Knowledge of scoring technology and methodologies; model development techniques and tools; advanced statistical methods and quantitative analysis; statistical tools and programs; fluency in SAS, WPL, R, Python or other similar programming language.
