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Data Science Lead - R01570082 en Brillio-2

Brillio-2 · Bangalore, Indien · Hybrid

Python

Swift

Cloud

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Description

Data Science Lead

Job requirements

With at least 8 years of experience in technical product management, engineering management, or similar roles leading technical teams in AI/ML or data-driven product development Key Responsibilities:
  • Set strategic priorities and determine team focus across AI Enablement and AI Experiments tracks, ensuring measurable progress toward organizational goals
  • Serve as the primary liaison with internal business teams to understand workflows, gather requirements, and translate business pain points into actionable technical work
  • Collaborate with product teams to align exploration and experimentation efforts with broader product direction
  • Lead the team’s operating rhythm, including stand-ups, demos, planning sessions, and progress readouts to leadership and stakeholders
  • Allocate resources across workstreams, moving team members based on shifting priorities to maximize impact and efficiency
  • Evaluate and shut down experiments or projects that are not delivering results, reprioritizing efforts swiftly and effectively
  • Guide the team’s technology roadmap by making decisions on model selection, infrastructure, build-vs-buy tradeoffs, and adoption of new tools
  • Define and evolve AI governance and compliance practices, establishing guardrails for responsible AI use, data handling, and decision explainability
  • Manage and optimize AI infrastructure spend, tracking LLM costs, token usage patterns, and vendor contracts to ensure cost-effective operations
    • Required Skills:
  • Advanced proficiency in Python for code review, scripting, and prototyping
  • Strong understanding of LLM-based systems, including retrieval-augmented generation pipelines
  • Experience with ML frameworks such as TensorFlow, PyTorch, and Sci-Kit Learn
  • Hands-on experience with Azure cloud infrastructure for deploying, monitoring, and scaling AI workloads
  • Expertise in statistical analysis and computing, including hypothesis testing, t-test, z-test, and regression techniques
  • Proficiency in forecasting techniques including exponential smoothing, ARIMA, and ARIMAX
  • Knowledge of classification algorithms such as decision trees and SVM
  • Familiarity with tools like KubeFlow and BentoML for ML lifecycle management
  • Understanding of probabilistic graph models and advanced distance metrics (Hamming, Euclidean, Manhattan)
    • Preferred Skills:
  • Experience with agent orchestration patterns for multi-step AI workflows
  • Expertise in prompt engineering to optimize output quality in LLM-based systems
  • Proficiency with Great Expectations and Evidently AI for data validation and monitoring
  • Experience defining AI governance frameworks for compliance and responsible data handling
    • Desired Qualifications:
  • Bachelor's degree in Computer Science, Data Science, Statistics, Information Technology, or a closely related discipline
  • Certification in Machine Learning, Data Science, or Artificial Intelligence from a recognized institution
  • Certification in Azure AI or Cloud Services (such as Microsoft Certified: Azure AI Engineer Associate)
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