Senior Data Scientist - Fraud Data Infrastructure & Automation

Accountabilities:

In this role, you will own end-to-end data science initiatives focused on fraud detection, identity verification, and scalable data infrastructure, ensuring both technical excellence and measurable business impact.

• Design, build, and maintain scalable data pipelines and workflows supporting analytics, fraud detection, and model development.

• Develop and deploy machine learning models using diverse data types such as tabular, text, images, and other structured/unstructured formats.

• Build and integrate agentic AI and LLM-based systems to automate data exploration, anomaly detection, and investigative workflows.

• Ensure data quality, integrity, and reliability through monitoring systems, validation frameworks, and anomaly detection mechanisms.

• Lead full ML and analytics lifecycle ownership, from problem definition through deployment and post-launch monitoring.

• Evaluate third-party data vendors and external datasets, designing experiments to assess quality, lift, and business value.

• Partner with Product, Engineering, and Risk teams to define requirements and deliver insights that shape fraud and identity strategy.

• Conduct advanced research into new data sources, algorithms, and fraud detection techniques.

• Communicate findings and recommendations to both technical and executive stakeholders with clarity and impact.

• Mentor peers and contribute to a culture of experimentation, learning, and high analytical standards.

Requirements:

The ideal candidate is a highly technical and impact-driven data scientist with strong experience in fraud, risk, or identity-related domains and a proven ability to deliver business outcomes from complex datasets.

• Master’s or PhD in a quantitative field (Computer Science, Statistics, Mathematics, Data Science) or equivalent experience.

• 5+ years of experience in data science, machine learning, or related roles in high-growth or fintech environments.

• Strong background in fraud prevention, risk modeling, or identity verification systems.

• Proven experience working with large-scale, messy, and real-world datasets to drive measurable impact.

• Proficiency in Python and SQL, with experience using ML frameworks such as PyTorch, TensorFlow, or scikit-learn.

• Deep understanding of ML techniques, model evaluation metrics, and data pipeline development.

• Experience building distributed data workflows using tools such as Spark, Airflow, or Databricks.

• Familiarity with evaluating third-party data sources and designing data quality and lift experiments.

• Experience with LLMs and agentic AI frameworks (e.g., LangChain, LangGraph, Ray) is highly preferred.

• Strong communication skills with the ability to translate complex technical findings into business insights.

• Ability to lead technical initiatives, influence cross-functional teams, and work autonomously.

Benefits:

• Opportunity to work on high-impact fraud detection and identity infrastructure challenges

• Remote-friendly work within approved US metro locations

• High ownership role with end-to-end responsibility for data science initiatives

• Exposure to advanced AI, LLMs, and agentic AI applications in production systems

• Collaborative environment with strong focus on innovation and technical excellence

• Opportunity to influence core product and risk decisioning systems

• Competitive compensation aligned with senior-level data science roles

• Work on large-scale, real-world datasets with direct business impact

• Strong culture of continuous learning, experimentation, and professional growth

How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
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