W
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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