Data Scientist

Pyramid It Consulting; Chennai District; On-site; INR 4,500,000 - 9,000,000; Full time

Job summary

Pyramid It Consulting in Chennai is seeking an Expert Data Scientist to lead evaluation-driven development across AI/ML and analytics platforms. You will define modeling strategy, evaluation frameworks, and governance for multiple 45-day release cycles while driving measurable business impact and mentoring senior data scientists.

You will own enterprise guidelines for synthetic data, offline experiments, and controlled validation, balancing performance, compliance, and cost across the portfolio.

Qualifications

• Master's or PhD in Data Science, Statistics, CS, OR, or related field
• 10+ years of experience delivering data science/ML/analytics solutions with leadership
• Proven ability to select modeling approaches across statistics, ML, optimization, simulation, and GenAI
• Deep experience defining evaluation metrics tied to KPIs and outcomes
• Extensive hands-on experience with AWS AI/ML platforms and MLOps at scale
• Experience leading agile, versioned delivery cycles across teams
• Experience balancing performance, explainability, compliance, and cost
• Experience designing synthetic data, offline experiments, validated programs
• Excellent stakeholder management and executive communication skills

Responsibilities

• Define evaluation-driven development standards and frameworks
• Champion guidelines for modeling approaches and validation methods
• Set enterprise standards for synthetic data, real-world validation, and data governance
• Own measurable improvements and KPI-driven portfolio outcomes
• Oversee multiple concurrent agile workstreams delivering measurable value
• Be escalation point for delivery risk and cross-team dependencies
• Partner with product/engineering to prioritize roadmap by impact and cost
• Set architecture and MLOps direction for AI/ML platforms on AWS
• Own cost-management and performance optimization for ML workloads
• Define enterprise approach to synthetic data, offline experimentation, and validation tooling
• Represent DS function in audits and regulatory reviews
• Mentor Senior Data Scientists and review evaluation frameworks
• Drive adoption of evaluation-driven development practices

Skills

Leadership

Executive communication

Stakeholder management

Mentoring

Evaluation-driven mindset

Education

Master's or PhD in Data Science or related field

Tools

AWS AI/ML platforms

MLOps

Model governance

Job description

Below exp is mandatory:

Modeling approaches(statistical, ML, optimization,simulation, GenAI where appropriate)

Synthetic data generation, offline experimentation, and controlled realworld validation.

AI/ML platforms (Amazon SageMaker AI, Google Cloud Vertex AI, and Microsoft Azure AI)

Note: Working on Synthetic data experience is Mandatory

Location - Chennai

Work Mode - Hybrid

Notice period - Immediate to 30 days

Interview process - Hackerrank+ Technical Interview+ Delivery Manager Discussion+ Client interview

Data Scientist - 70%, AI/ML - 30%,

Domain - Healthcare & life sciences

About the role:

As an Expert Data Scientist, become a part of a cross-functional development team engineering experiences of tomorrow. The Expert/Principal Data Scientist is a senior technical leader responsible for setting the standard for evaluation-driven development across the organization's AI/ML and analytics portfolio. This person defines modeling strategy, evaluation frameworks, and delivery governance across multiple 45-day release cycles, and is accountable for demonstrating measurable business impact at a portfolio level while mentoring senior and mid-level data scientists.

Responsibilities:

• Evaluation-Driven Development Strategy & Standards
• Define and champion the organization's evaluation-driven development framework: standards for selecting modeling approaches (statistical, ML, optimization, simulation, GenAI), evaluation metric design, and validation methodology
• Establish enterprise guidelines for aligning evaluation metrics to business and process outcomes, ensuring consistency across teams and products
• Set standards for the use of synthetic data, historical data, and real-world/controlled validation across the model lifecycle, including approval gates before production rollout
• Own the definition of \"measurable improvement\" for the portfolio — ensuring every release is backed by a rigorous before/after comparison against business KPIsDelivery Leadership
• Oversee and be accountable for multiple concurrent workstreams delivered through 45-day versioned agile cycles, ensuring the portfolio consistently ships incremental, measurable value
• Act as the escalation point for delivery risk, technical trade-offs, and cross-team dependencies across release cycles
• Partner with product and engineering leadership to prioritize the roadmap based on expected business impact vs. delivery cost/riskPlatform, MLOps & Cost
• Set architectural and MLOps direction for AI/ML platforms and analytics products on AWS, including model deployment patterns, monitoring, and automated governance
• Own cost-management and performance-optimization strategy for data and ML workloads at scale, setting budgets and efficiency targets across teams
• Define enterprise approach to synthetic data generation, offline experimentation, and controlled real-world validation, including tooling selectionGovernance & Compliance
• Own the framework for balancing model performance, explainability, regulatory compliance, and cost across the portfolio, including escalation criteria for high-risk models
• Represent the data science function in audits, regulatory reviews, and executive reporting on model governance and business impactLeadership
• Mentor Senior Data Scientists and review their evaluation frameworks, modeling choices, and delivery outcomes
• Drive adoption of best practices in evaluation-driven development across the organization

Requirements:

• Master's or PhD in Data Science, Statistics, Computer Science, Operations Research, or related field (or equivalent demonstrated experience)
• 10+ years of experience delivering data science/ML/analytics solutions, including leadership of technical strategy at a portfolio or platform level
• Proven track record of selecting and justifying modeling approaches across statistical, ML, optimization, simulation, and GenAI paradigms based on business context
• Deep experience defining evaluation metrics tied to business and process KPIs, and demonstrating measurable outcomes from delivered models
• Extensive hands-on and architectural experience with AWS AI/ML platforms and MLOps practices at scale
• Demonstrated ownership of agile, versioned delivery cycles across multiple teams or products
• Strong track record balancing model performance, explainability, compliance, and cost trade-offs, including in regulated environments
• Experience designing synthetic data strategies, offline experimentation frameworks, and controlled real-world validation programs
• Excellent stakeholder management and executive communication skills

Desirable:

• Experience presenting model governance and impact metrics to executive or regulatory audiences
• Publications, patents, or public speaking in applied ML/AI evaluation methodology
• Experience building or scaling MLOps platforms from the ground up