- Apply data science and machine learning techniques to projects and business-relevant analysis and research to enable solving complex business problems and driving business decisions using state-of-the-art techniques.
- Build data predictive, prescriptive and descriptive analytics models and surface key insight to drive decision making across the organization.
- Identify the right models and select the right parameters to solve a problem for statistical models and machine learning models.
- Identify, predict and model customer behavior, and convey analytics findings to key business stakeholders.
- Identify and integrate new datasets that can be leveraged to address business area needs.
- Create repository of analytics models and assets to be leveraged for future usage to support business applications, ensuring system scalability, security, performance, and reliability.
- Build and maintain a large-scale analytics infrastructure to be used across the business and consistently conduct research, design, implementation, and validation of cutting-edge algorithms in order to analyze diverse data sources in order to enable desired business outcomes.
- Support the implementation of best programming practices and sharing of data science skills and knowledge across the organization.
- Advise on transformative business strategies through the measurement, manipulation, reporting and dissemination of broad sets of data.
- Prepare analysis and presentations for the Chief Data Scientist and relevant stakeholders to communicate analytics models in business language that will give insights for departmental as well as business-wide decision making.
- Keep up to date with the technical developments and their applications in the financial services sector.
- Bachelor’s degree in Data Science, Actuarial Science, Mathematics, Statistics, Computer Science, Computer Engineering, Management of Information and Communication Technology, Business Informatics, or equivalent combination of education and experience.
- Master’s degree in Data Science, Data Analytics, Statistics, Applied Mathematics, Computer Science, Computer Engineering, Operations Research, or related discipline is preferred.
- Experience working in the financial services sector is preferred
- 0-2 years’ experience in data science, machine learning, or data analytics role
- Proficiency with data mining and statistical analysis
- Advanced pattern recognition and predictive modelling experience
- Data management experience, including sourcing, cleaning and linking different datasets.
- Experience working with granular, messy and/or textual data
- Fluency in at least one mainstream programming language (for example, Python, R), and with good SQL skills
- Experience with at least one of the following data visualization tools: Tableau, Power BI
- A strong ability to communicate analytical outputs to non-technical audiences in a clear but rigorous way, both verbally and in writing
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