Responsibilities

Build ML Based Fraud and Risk models to reduce risk related loss and increase pass rate
Develop and foster a rigorous data-driven culture within the Risk & Compliance teams
Conduct research and deep-dive data analysis to find different areas of identified and unidentified risks to quantify exposure and suggest data-driven mitigation insights to reduce risks
Design and analyze A / B experiments to evaluate the impact of changes and the risk models deployed
Create new risk signals that would result in detecting fraud, transaction monitoring and identifying malicious trading activity
Define, measure and consistently improve all essential monitoring metrics for the Risk & Compliance
Conceptualize and build / prototype models / solutions in R / Python focused on Financial Crime & Regulatory Compliance
Provide technical leadership to the rest of the Risk & Compliance teams
Design and build tools for the Risk team that help to automate processes and facilitate smart decision making
Conducting ad-hoc analysis to identify and mitigate risk and fraud
Collaborate with other teams like product to ensure swift implementation of risk modules

Requirements

3+ years prior experience in Financial Risk
4+ years in Data Science / Analytics
Proficient with SQL and expertise with R or Python
Experience in building ML based Fraud and Risk models
Experience in designing and developing compelling data visualizations and dashboards
Excellent understanding of Risk Analytics and Fraud Models
Ability to translate complex data into actionable insights for a non-technical audience
Experience in a high-growth tech environment
A deep understanding of statistical concepts
Bachelor degree in Computer Science, Statistics, Economics, Mathematics, Operation Research, Engineering is preferred
Prior experience at a tech company is a plus

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