TekWissen is looking for an Associate Fraud Strategy Data Scientist to support the Fraud Risk Strategy team in developing and managing fraud detection, risk analysis, and loss mitigation strategies for a client's .com platform. The role aims to address emerging fraud trends while ensuring a positive customer experience.
Requirements
- Proficiency in SQL, Python, Excel including key data science libraries
- Proficiency in data visualization including Tableau
- Experience working with large datasets
- Experience using statistics and data science to solve complex business problems
- Desirable to have experience or aptitude solving problems related to risk using data science and analytics
- Bonus: Experience with AWS, knowledge of fraud investigations, payment rule systems, working with ML teams, fraud typologies
- Data analytics and models
Responsibilities
- Develop python scripts and models that support strategies
- Design rules to detect/mitigate fraud
- Utilize data analysis to design and implement fraud strategies
- Collaborate with cross-functional stakeholders including product managers and engineering teams to deploy data-driven fraud solutions that operate at scale and in real time for end customers.
- Development of dashboard and visualizations to track KPI of fraud strategies implemented
- Work with product/engineering to improvement control capabilities
- Develop and present strategies and guide execution
Other
- Maximum 2 years of experience in risk analytics, data analysis, and data science within relevant industry experience in eCommerce, online payments, user trust/risk/fraud, or investigation/product abuse.
- Bachelor's degree in Data Analytics, Data Science, Mathematics, Statistics, Data Mining or related field or equivalent practical experience
- Ability to clearly communicate complex results to technical experts, business partners, and executives including development of dashboards and visualizations, ie Tableau.
- Comfortable with ambiguity and yet able to steer analytics projects toward clear business goals, testable hypotheses, and action-oriented outcomes
- Demonstrated analytical thinking through data-driven decisions, as well as the technical know-how, and ability to work with your team to make a big impact.
