1 month ago
Job Summary
With the ever-expanding data sets and techniques to handle data, in this role you will use cutting edge techniques in domain languages to handle both traditional and alternative data sets and apply them into credit modelling. We are innovating the way the essential intelligence is being collected and processed to support our clients’ decision making and risk monitoring needs. By leveraging the data science oriented technologies, we are delivering solutions faster and at scale, while maintaining the top notch quality standards.
- Minimum Qualification:Degree
- Experience Level:Senior level
- Experience Length:5 years
Job Description/Requirements
Responsibilities:
- Leading the design, architecture, ML pipeline development for Universal Coverage.
- Design, execute and deploy projects aimed at solving high-impact business problems.
- Play a central role in all stages of the data science project life cycle, including:
- Identification of suitable data science project opportunities
- Partnering with business leaders, domain experts, and end-users to gain business understanding, data understanding, and collect requirements
- Evaluation/interpretation of results and presentation to business leaders
- Partnering with software developers to provide specifications for deploying models/algorithms into production systems, when applicable
- Perform exploratory data analysis, proof-of-concept modeling, and business cases necessary to generate partner consensus and internal support for your projects
- Dedicatedly communicate the vision and status of your data science projects, ensuring that accurate expectations are set and met across all levels of partners
- Present to customers projects and validate needs and requirements to feed into the business case
- Provide analysis and due diligence expertise with potential strategic partners
Requirements:
- 5+ years' experience in a quantitative, Data Science or other advanced data & predictive analytics role
- Practical experience with data mining, machine learning techniques, natural language processing, and data visualization - with an explicit aspiration to significantly enhance own skillset in those fields
- Experience of working on end-to-end data science pipelines: problem scoping, data gathering, exploratory data analysis, modelling, insights, visualizations, monitoring and maintenance
- Proven track record of strong analytical skills, learning agility, and independent thinking. Ability to make observations, form an option, and articulate to the team
- Typically requires a Graduate Degree in Math, Statistics, Engineering, Operational Research, or related field
- Strong English-speaking and writing skills required
- Hands on experience with implementing statistical models
- Experience in applying optimization and numerical methods
- Hands on experience with implementing Machine Learning techniques in a specific business application context.
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