Data Science Lead - R01570082

Brillio; Bengaluru; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Brillio is seeking a Data Science Lead to drive strategic AI initiatives and lead technical teams in Bengaluru. The role focuses on AI Enablement and AI Experiments, coordinating with business units to translate requirements into scalable AI solutions.

You will steer governance, tooling, and infrastructure choices while managing budgets and vendor relationships. The ideal candidate has 8+ years in technical leadership, deep expertise in Python and ML frameworks, and a strong track record in

Qualifications

• 8+ years in technical product management, engineering management, or similar roles leading technical teams in AI/ML or data-driven product development.
• Strong leadership of AI/ML or data-driven products and teams.
• Proficiency in Python for code review and prototyping.
• Deep knowledge of LLM-based systems and retrieval-augmented generation pipelines.
• Hands-on experience with TensorFlow, PyTorch, Sci-Kit Learn.
• Experience with Azure cloud infrastructure for deploying, monitoring, and scaling AI workloads.
• Expertise in statistical analysis and computing: hypothesis testing, t-test, z-test, regression.
• Forecasting methods: exponential smoothing, ARIMA, ARIMAX.
• Knowledge of classification algorithms (decision trees, SVM).
• Familiarity with ML lifecycle tools like KubeFlow and BentoML.
• Understanding of probabilistic graph models and distance metrics (Hamming, Euclidean, Manhattan).
• Experience with agent orchestration patterns and prompt engineering for LLMs.
• Data validation/monitoring tools (Great Expectations, Evidently AI).
• Experience defining AI governance frameworks for compliance and responsible data handling.

Responsibilities

• Set strategic priorities across AI Enablement and AI Experiments tracks with measurable progress toward goals.
• Liaise with internal business teams to translate workflows into actionable technical work.
• Collaborate with product teams to align experiments with broader product direction.
• Lead the team's operating rhythm: stand-ups, demos, planning sessions, progress readouts to leadership.
• Allocate resources across workstreams to maximize impact and efficiency.
• Evaluate and shut down experiments not delivering results; reprioritize swiftly.
• Guide the technology roadmap: model selection, build-vs-buy decisions, new tools adoption.
• Define and evolve AI governance and compliance practices for responsible AI use.
• Manage and optimize AI infrastructure spend, tracking LLM costs and vendor contracts.

Skills

Python

LLM systems

Statistical analysis

Forecasting methods

Classification algorithms

ML pipelines

Prompt engineering

AI governance

Education

Bachelor's in CS/DS/Stats

ML/Data/AI Certification

Azure AI Certification

Tools

TensorFlow

PyTorch

Sci-Kit Learn

Azure

KubeFlow

BentoML

Great Expectations

Evidently AI

Job description

Data Science Lead

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)