# Data Science Lead - R01570082 at Brillio

Data Science Lead - R01570082 at Brillio in Bangalore, Karnataka, India. Posted September 2, 2026.

- Company: Brillio
- Location: Bangalore, Karnataka, India
- Experience: 8+ years
- Posted: 2026-09-02
- Apply: https://jobs.lever.co/brillio-2/06f3848e-d618-43fb-bb3c-1c5a10d556c4/apply
- Source: https://jobmagic.ai/jobs/data-science-lead-r01570082-brillio-x4asj5

## Requirements

- 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
- 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

## 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)