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Salary
≈ $23k – $49k per year (Estimated)
Location
In office (Gurgaon)
Seniority
Senior · 5+ years exp

First seen by Alion on Sep 25, 2026.

Overview
Company
Impact
Profile match
Sign3 is a B2B fintech and cybersecurity firm that offers a real-time AI fraud detection and risk intelligence platform to help companies prevent scams, reduce financial losses and make safer decisions about users.

We are looking for a Senior Data Scientist to build and deploy machine learning models that power fraud detection, risk scoring, and credit decisioning for our fintech and banking partners. You will own the end-to-end model lifecycle, from data exploration and feature engineering to deployment, monitoring, and iteration, while working closely with engineering and product teams.

Responsibilities:

  • Develop machine learning and statistical models for fraud prevention, risk scoring, and credit underwriting.
  • Analyze large-scale behavioral and transactional datasets to identify patterns, anomalies, and emerging fraud trends.
  • Design and run experiments to evaluate, compare, and improve model performance.
  • Partner with engineering to deploy models into production and ensure they are reliable, observable, and performant at scale.
  • Monitor live models for drift and degradation, and lead retraining and improvement cycles.
  • Collaborate with product and risk teams to translate business problems into modeling solutions.

Requirements:

  • Bachelor's degree or higher in computer science, statistics, applied mathematics, or a related field.
  • 5+ years of experience in data science, with exposure to fintech or financial services preferred.
  • Strong expertise in Python and SQL, and hands-on experience with ML frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow.
  • Solid foundation in classical machine learning, statistical modeling, and experiment design.
  • Experience taking models from notebook to production, including monitoring and iteration.
  • Ability to communicate complex findings clearly to technical and non-technical stakeholders.
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