In this role you will use advanced Machine Learning techniques to mitigate fraud across various payment channels such as Digital Transactions including Quick Pay , Quick Deposit, Credit Card, Debit Card and Checks. You will work closely with business analysts, product owner and operations to find tangible opportunities to prevent fraud, enhance customer experience and provide insights which will allow us to assess the risk of portfolio in several dimensions. If you are intellectually curious and have a passion for driving solutions across organizational boundaries, you may be the perfect fit for our team
Job Responsibilities:
- Work on some of the most complex problems imaginable at the intersection Digital, Machine Learning and Fraud. Interact with insanely large and fascinating data to solve real world problems
- Develop analytical strategies that can significantly change how fraud is managed and set the path for future
- Will help build a foundation of state-of-the-art technical and scientific capabilities to support a number of ongoing and planned data analytics projects:
- Research, design, implement, and evaluate machine learning approaches and models
- Perform ad-hoc exploratory statistics and data mining tasks on diverse datasets from small scale to œbig data
- Investigate data visualization and summarization techniques for conveying key findings
- Communicate findings and obstacles to stakeholders to help deliver the results
Required Qualifications, Skills and Capabilities
- Minimum Master™s Degree with preferred concentrations in Mathematics, Statistics, Computer Science, Physical Science, Engineering, or other quantitative discipline; PhD preferred
- At least 2-4 years of hands-on experience as a data scientist, and advanced proficiency in Python; prior PySpark experience preferred
- Fundamental understanding of probability and statistics
- Hands-on experience in Machine Learning algorithm development using large scale data
- Desire to use modern technologies as a disruptive influence for solving large scale business problems
Preferred Qualifications, Skills and Capabilities
- Experience in Amazon Web Services
- Statistical modeling using machine learning techniques.
Keyword: card%20services
In this role you will use advanced Machine Learning techniques to mitigate fraud across various payment channels such as Digital Transactions including Quick Pay , Quick Deposit, Credit Card, Debit Card and Checks. You will work closely with business analysts, product owner and operations to find tangible opportunities to prevent fraud, enhance customer experience and provide insights which will allow us to assess the risk of portfolio in several dimensions. If you are intellectually curious and have a passion for driving solutions across organizational boundaries, you may be the perfect fit for our team
Job Responsibilities:
- Work on some of the most complex problems imaginable at the intersection Digital, Machine Learning and Fraud. Interact with insanely large and fascinating data to solve real world problems
- Develop analytical strategies that can significantly change how fraud is managed and set the path for future
- Will help build a foundation of state-of-the-art technical and scientific capabilities to support a number of ongoing and planned data analytics projects:
- Research, design, implement, and evaluate machine learning approaches and models
- Perform ad-hoc exploratory statistics and data mining tasks on diverse datasets from small scale to œbig data
- Investigate data visualization and summarization techniques for conveying key findings
- Communicate findings and obstacles to stakeholders to help deliver the results
Required Qualifications, Skills and Capabilities
- Minimum Master™s Degree with preferred concentrations in Mathematics, Statistics, Computer Science, Physical Science, Engineering, or other quantitative discipline; PhD preferred
- At least 2-4 years of hands-on experience as a data scientist, and advanced proficiency in Python; prior PySpark experience preferred
- Fundamental understanding of probability and statistics
- Hands-on experience in Machine Learning algorithm development using large scale data
- Desire to use modern technologies as a disruptive influence for solving large scale business problems
Preferred Qualifications, Skills and Capabilities
- Experience in Amazon Web Services
- Statistical modeling using machine learning techniques.
Keyword: card%20services
