Data Scientist – Fraud
Company Name:-
Radial, Inc.
Job Location:-
King of Prussia, PA 19406
Job Summary:-
Radial, Inc.
, a bpost group company, is the leader in omnichannel commerce technology and operations.
Premier brands around the world confidently partner with Radial to deliver their brand promises, anticipate and respond to industry disruption, and compete in a rapidly evolving market.
Radial’s innovative solutions connect retailers and customers through advanced omnichannel technologies; intelligent payments and fraud protection; efficient fulfillment, supply chain services; and insightful customer care services especially where high-value customer experiences are critical.
We are flexible, scalable, and focused on our clients’ business objectives.
The Data Scientist will work with our Sr.
Manager of Advanced Analytics and Data Science as well as our fraud rules, fraud review team, technology, product, policy, and client relationship partners to build, deploy, and maintain advanced analytical solutions with the goal of reducing fraud chargebacks, reducing false positive decline, improving client experience, and ensuring that Radial minimizes its total cost of fraud while minimizes friction to the merchant and consumer.
Responsibilities:
Manage machine learning model life cycle through model audit, back testing, forward testing, benchmarking with the help of performance metrics
Conduct exploratory data analysis, supervised, unsupervised and semi-supervised machine learning to identify fraud trend, segment and clusters, and optimization opportunity
Robotic process automation to reduce the need for manual, repeatable processes
Work closely with Technology team for model deployment and monitoring
Work with the other data scientists and the team executive and stakeholders to help develop the data strategy for client protection to ensure the organization has the proper data to make the right decisions, with a priority on data availability in real-time, and generating true customer-level views able to make intelligent fraud decisions leveraging the entirety of our interactions with a customerRequirements:
Strong programming skills in SQL, Python, R and Microsoft 365 Tools (Excel, Word, Power Point, etc.
)
Strong knowledge of machine learning and anomaly detection algorithms including Regressions, Random Forrest, GBM
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