Research Scientist II (Fraud)

About the role

The Research Scientist II on the Fraud Research team at Pindrop will help improve how the company detects, scores, and investigates fraud and scams across voice and Interactive Voice Response (IVR) interactions. This role involves building and improving fraud risk models and scoring systems using a combination of audio, behavioral, and metadata-based signals. The individual will also analyze fraud patterns across customer environments and translate findings into measurable improvements in model performance, investigation workflows, or mitigation strategies.

Responsibilities

• Build and improve fraud risk models and scoring systems using a combination of audio, behavioral, and metadata-based signals.
• Analyze fraud patterns across customer environments and translate findings into measurable improvements in model performance, investigation workflows, or mitigation strategies.
• Research and build a scam detection stack, from conception to realization. Partner with engineering and cross-functional teams to move successful research into production and improve fraud outcomes in live environments.
• Support high-priority fraud investigations by analyzing system behavior, fraudster attack patterns, and detection gaps, then recommending practical next steps for our customers.
• Improve the quality and precision of fraud-related identity signals, including voice-based indicators and repeat-offender detection.
• Design and maintain reproducible research workflows, internal tools, and evaluation pipelines that help the team experiment efficiently and measure impact clearly.
• Contribute to technical reviews, knowledge sharing, and research documentation that helps the broader organization understand and apply your work.
• Contribute to adjacent innovation areas, including emerging AI-assisted fraud-analysis workflows, when relevant to team priorities.

Requirements

• Advanced Degree (Master’s or PhD) in Computer Science, Mathematics, Statistics, Engineering, Artificial Intelligence, or a related quantitative field, or equivalent applied research experience.
• 3+ years of professional experience in machine learning, large-language models, fraud detection, natural language processing, risk modeling, speech or signal processing, anomaly detection, or a closely related domain.
• Strong Python skills and experience building research tooling, experimentation frameworks, or model evaluation workflows.
• Hands-on experience with modern machine learning frameworks such as PyTorch, TensorFlow, or Keras.
• A track record of translating research findings into practical improvements, whether in models, decision systems, or production-facing recommendations.
• Foundational knowledge of fraud, identity, consumer scams, authentication, risk scoring, or customer security concepts.

Qualifications

• Persistent, curious, and scientifically rigorous, especially when working through ambiguous data, noisy signals, or fast-evolving fraud behavior.
• Comfortable owning research workstreams from problem definition through experimentation, analysis, and recommendation.
• Communicate clearly with both technical and non-technical partners, and explain tradeoffs, assumptions, and results in a practical way.
• Care deeply about reproducibility, documentation, and building research that can stand up in real production settings.
• Motivated by high-impact security and fraud problems and wanting your work to influence real customer outcomes.

Skills

• Advanced Degree (Master’s or PhD) in Computer Science, Mathematics, Statistics, Engineering, Artificial Intelligence, or a related quantitative field, or equivalent applied research experience.
• 3+ years of professional experience in machine learning, large-language models, fraud detection, natural language processing, risk modeling, speech or signal processing, anomaly detection, or a closely related domain.
• Strong Python skills and experience building research tooling, experimentation frameworks, or model evaluation workflows.
• Hands-on experience with modern machine learning frameworks such as PyTorch, TensorFlow, or Keras.
• A track record of translating research findings into practical improvements, whether in models, decision systems, or production-facing recommendations.
• Foundational knowledge of fraud, identity, consumer scams, authentication, risk scoring, or customer security concepts.

Benefits

• Competitive compensation package, including RSUs (Restricted Stock Units) for all employees, so everyone shares in our long-term success.
• Remote-first environment - giving you flexibility and autonomy in how you structure your day.
• Unlimited Paid Time Off (PTO).
• Generous health and welfare plans to choose from - including one employer-paid "employee-only" plan!
• Low-cost vision and dental plans for you and your family, providing comprehensive coverage and peace of mind.
• Paid Parental Leave - Including birth, adoptive & foster parents.
• Annual Learning & Development stipend to support your professional growth, skill-building, certifications, and continued education.