Job Description
As a data scientist in the Risk Data Science team, you will develop data science models by working with large-scale data to derive new intelligence and use cutting-edge data science techniques. You will partner with Risk, product, and engineering stakeholders to identify and solve some of the most impactful and stimulating business problems. You will work in a fast-paced environment with direct impacts to the business.
Good To Have:
- Experience in credit and fraud risk
- Experience in alternative data sources (especially FinTech)
- PhD
Must Have:
- Combine technical and business knowledge to develop innovative data science solutions for Financial Technology
- Rapidly prototype solutions and contribute to product and feature discussions
- Analyse large volumes of data and generate actionable insights
- Experiment with different ML techniques and research the latest technologies (e.g. LLM) to determine the best approach
- Own end-to-end solutions, from formulating the technical problem to deployment of the solution as part of a cross-functional team of scientists, analysts, product managers, and engineers
- At least 3 years of experience developing ML solutions
- Strong quantitative and problem-solving skills
- Solid understanding of Statistics/ML fundamentals and experience in Python + SQL
- Communication skills to engage with business stakeholders to understand their needs and effectively communicate the results of the analytical solutions
- Ability to write clear and concise technical documentation
- Bachelors or Masters in a quantitative discipline
About the Role
As a data scientist in the Risk Data Science team, you will develop data science models by working with large-scale data to derive new intelligence and use cutting-edge data science techniques. You will partner with Risk, product, and engineering stakeholders to identify and solve some of the most impactful and stimulating business problems. You will work in a fast-paced environment with direct impacts to the business.
What You Will Do
- Combine technical and business knowledge to develop innovative data science solutions for Financial Technology
- Rapidly prototype solutions and contribute to product and feature discussions
- Analyse large volumes of data and generate actionable insights
- Experiment with different ML techniques and research the latest technologies (e.g. LLM) to determine the best approach
- Own end-to-end solutions, from formulating the technical problem to deployment of the solution as part of a cross-functional team of scientists, analysts, product managers, and engineers
What You Will Need
- At least 3 years of experience developing ML solutions
- Experience in credit and fraud risk a plus
- Experience in alternative data sources (especially FinTech) a plus
- Strong quantitative and problem-solving skills
- Solid understanding of Statistics/ML fundamentals and experience in Python + SQL
- Communication skills to engage with business stakeholders to understand their needs and effectively communicate the results of the analytical solutions
- Ability to write clear and concise technical documentation
- Bachelors or Masters in a quantitative discipline. PhD a plus
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