Fraud / Credit Data Scientist, Risk Solutions
WFA Digital Insight
As the demand for skilled data scientists in the fintech industry continues to rise, with a reported 25% increase in 2025, companies like name are on the hunt for top talent to drive their risk management strategies forward. With a strong focus on machine learning and artificial intelligence, this role is perfect for those who excel in identifying and mitigating risks. name stands out for its commitment to leveraging cutting-edge technologies to inform decision-making, making this an exciting opportunity for candidates looking to make a real impact. Before applying, candidates should be prepared to showcase their analytical prowess, creative problem-solving skills, and ability to communicate complex ideas effectively.
Job Description
About the Role
The Global Risk Solutions and Strategy group at name is a dynamic team dedicated to optimizing risk solutions and models, playing a critical role in enabling the company's strategic objectives. As a Fraud / Credit Data Scientist, you will be at the forefront of developing and implementing data-driven risk management strategies, utilizing machine learning and statistical frameworks to inform decision-making across the client lifecycle. Your expertise in data science will be invaluable in helping the firm identify, measure, and proactively manage credit, collections, and fraud risk. You will work closely with stakeholders and domain experts, driving better decision-making through the application of advanced data science methodologies and technologies.In this role, you will thrive in a fast-paced, collaborative environment, working alongside a team of like-minded professionals who share your passion for data science and risk management. The company's commitment to innovation and excellence provides a unique opportunity for growth and professional development, as you contribute to the development of cutting-edge risk management solutions.
What You Will Do
- Develop and implement machine learning models and algorithms to identify and mitigate risks
- Collaborate with stakeholders to design and implement risk management strategies
- Analyze large datasets to extract insights and inform business decisions
- Design and develop automated processes to combine and transform data from disparate sources
- Stay abreast of emerging trends in machine learning and identify opportunities to leverage new tools
- Communicate complex analytical findings to stakeholders
- Develop and maintain datasets and data systems to support risk management initiatives
- Work closely with cross-functional teams to drive business outcomes
- Participate in the development of the team's best practices and processes
- Contribute to the design and implementation of data visualizations and reporting tools
What We Are Looking For
- 1-3 years of hands-on experience in data science, machine learning, or artificial intelligence
- Excellent analytical, creative problem-solving, and critical thinking skills
- Master's or Ph.D. degree in a quantitative field such as mathematics, statistics, data science, operations research, or computer science
- Advanced knowledge of SQL and experience creating and managing large datasets
- Working knowledge of Python or R and experience with data science libraries
- Strong communication and presentation skills
- Ability to work collaboratively and independently in a self-starting manner
- Experience in the fintech or financial services industry is preferred
Nice to Have
- Experience with cloud-based data platforms
- Familiarity with agile development methodologies
- Certification in data science or a related field
Benefits and Perks
- Competitive compensation package
- Opportunities for professional growth and development
- Collaborative and dynamic work environment
- Access to cutting-edge technologies and tools
- Flexible working hours and remote work options
- Comprehensive health and wellness benefits
- Generous paid time off and holiday leave
How to Stand Out
- Ensure your resume and cover letter showcase your analytical and problem-solving skills, highlighting specific examples of risk management strategies you've developed and implemented.
- Develop a portfolio that demonstrates your expertise in machine learning and data science, including any relevant projects or certifications.
- Be prepared to discuss your experience working with large datasets and your ability to communicate complex analytical findings to stakeholders.
- Research the company and the role thoroughly, and be prepared to ask informed questions during the interview process.
- Consider highlighting any experience you have working in the fintech or financial services industry, and be prepared to discuss how your skills and experience align with the company's strategic objectives.
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