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Lead Data Scientist

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Onsite

Lead Data Scientist

Wenger & Watson

Lead Data Scientist

Skills

SQL QueriesData EngineeringPythonData SciencePyTorchTensorFlowRData AnalysisMachine LearningAIAWSNLP / Natural Language ProcessingComplianceRegulatory ComplianceAzure

22 days ago

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Important information


Contract type:

Permanent

Location:

Bengaluru, Karnataka, India

Work mode:

Onsite

Published on:

12 October 2026

What they need


Required Skills:

  • 8–12 years of experience in data science or related analytics and statistical modelling roles.
  • Own and drive end‑to‑end AI/ML solutions—from problem definition and experimentation to production deployment and continuous optimization
  • Define and lead technical strategy, including model selection, evaluation metrics, and trade‑offs across performance, scalability, and constraints
  • Design and deliver advanced AI solutions (including NLP, LLMs, GenAI, and RAG) aligned with business outcomes
  • Act as the primary technical authority, guiding data scientists and ML engineers while proactively identifying and resolving risks
  • Establish and sign off on success criteria, including model evaluation metrics, quality benchmarks, and production readiness standards
  • Ensure Responsible AI compliance, including governance, explainability, documentation, and audit readiness
  • Collaborate with engineering teams to enable secure, scalable, and reliable production deployments using MLOps and CI/CD best practices
  • Lead and mentor senior data scientists, driving full‑stack data science delivery and fostering strong problem‑solving and algorithmic thinking
  • Apply deep technical expertise in Python, ML/DL frameworks (TensorFlow, PyTorch, Scikit‑learn), and large‑scale data processing
  • Leverage strong foundations in statistics, data engineering, and cloud platforms (Azure/AWS) for production-grade solutions
  • Translate business requirements into technical solutions and influence cross‑functional stakeholders to drive strategic outcomes

Preferred

  • Experience working within large investment banking or financial services organizations.
  • Experience defining enterprise AI governance, ethics guidelines, risk frameworks, or regulatory compliance programs.
  • Published research, patents, or conference presentations in AI, ML, NLP, or related fields.
  • Experience leading multi‑team or matrixed delivery organizations across regions and time zones.
  • Industry reputation as a technical expert or AI thought leader.

Education:

  • Master’s degree in Statistics, Mathematics, or Computer Science with a Data Science certification, or an Engineering degree specializing in Data Science and Artificial Intelligence.
  • Proficiency in programming languages such as Python, R, and SQL

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