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6-8 Years
Not Disclosed
Early Applicant
  • Posted 8 hours ago
  • Be among the first 10 applicants

Job Description

Senior Data Scientist

Key Responsibilities

  • Design and develop state-of-the-art deep learning models for biometric recognition (facial, fingerprint, iris) and fraud detection using convolutional neural networks (CNNs), transformers, and hybrid architectures
  • Lead the design of end-to-end AI pipelines: data ingestion, pre-processing, model training, evaluation, and deployment in production environments
  • Conduct thorough error analysis, A/B testing, and performance evaluations to identify weaknesses and improve recognition accuracy and system efficiency
  • Architect scalable data pipelines for image and biometric signal cleaning, feature extraction, clustering, and deduplication at national scale
  • Collaborate with domain experts, biometric vendors, and legal/policy teams to ensure technological solutions are interpretable, robust, and policy compliant
  • Monitor system drift, adversarial threats, and fraud patterns in biometric usage across the Aadhaar ecosystem
  • Publish internal technical reports and participate in peer-reviewed research where appropriate
  • Mentor and guide junior data scientists and ML engineers in best practices

Education

  • B.Tech / B.E. from a Tier-1 Institution (IITs, IISc, IIITs, BITS, NITs, or similar institutions), preferably in Computer Science, IT, Electronics Engineering, Electrical Engineering, Mathematics, or a related field

Experience & Skills

  • Minimum 6+ years of hands-on experience in machine learning, deep learning, or computer vision roles
  • Strong expertise in deep learning frameworks such as PyTorch, TensorFlow, and Keras
  • In-depth knowledge of CNNs, Transformers, Siamese networks, contrastive learning, and embedding space analysis
  • Proficient in Python and experienced with large-scale data processing tools like Spark, Dask, or Hadoop
  • Prior experience working with biometric or image datasets (face, iris, fingerprint) is desirable
  • Strong understanding of data cleaning, clustering (e.g., DBSCAN, K-Means), anomaly detection, and unsupervised learning
  • Knowledge of privacy-preserving techniques such as federated learning, differential privacy, and homomorphic encryption is a plus
  • Proven record of taking models from research into production at scale, with MLOps exposure (Docker, Kubernetes, MLflow, model monitoring and drift detection)
  • Experience on large-scale government or public digital infrastructure programmes is a plus

What We Offer

  • A unique opportunity to work on the largest biometric identity system in the world
  • Access to UIDAI's unparalleled scale of identity data and secure research environments
  • Competitive compensation and benefits tailored for top-tier AI talent in the public sector
  • A mission-driven organization with direct impact on national-scale governance, security, and inclusion

Key Skills

Convolutional Neural Networks (CNNs)

MLflow

Contrastive learning

Dask

Differential privacy

Drift detection

Homomorphic encryption

Siamese networks

Federated learning

Embedding space analysis

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