Job Description
Role Overview
We are seeking a highly experienced AI & Data Architect / Technical Lead to
lead an enterprise engagement focused on Pricing Elasticity Modeling,
Customer Segmentation, and AI-driven Supply Chain Intelligence.
This role will serve as the primary technical and analytics lead for pricing
transformation initiatives, driving the design and implementation of advanced
pricing models, elasticity engines, segmentation frameworks, and scalable
enterprise architecture.
While Databricks and Data Architecture expertise are strongly preferred (not
mandatory), the core emphasis of this role is pricing intelligence, business
alignment, architectural vision, and enterprise-grade execution.
The ideal candidate combines deep expertise in pricing analytics, strong
understanding of AI models and modern architecture patterns, business process
fluency, on-site leadership capability, innovation mindset, and mentoring
strength.
Primary Responsibilities – Pricing Elasticity & Advanced Analytics
(Core Focus)
• Design, build, and operationalize price elasticity models across product
categories.
• Develop demand forecasting and price sensitivity models using statistical,
econometric, and ML approaches.
• Implement cross-elasticity analysis across SKUs and customer segments.
• Build dynamic pricing engines integrated with ERP and business systems.
• Establish model monitoring, recalibration frameworks, and continuous
optimization processes.
• Translate pricing strategy into production-grade AI-driven systems.
Customer Segmentation & Business Process Understanding
• Design and deploy advanced customer segmentation frameworks
(behavioral, value-based, RFM, clustering, predictive segmentation).
• Apply ML techniques such as clustering, classification, and propensity
modeling.
• Demonstrate strong understanding of business processes and operational
flows.
• Speak the language of business stakeholders (similar to ERP functional
consultants or business analysts).
• Align pricing and segmentation outputs with revenue, margin, and supply
chain KPIs.
Data Architecture & Platform Engineering (Databricks Strongly
Preferred)
• Architect scalable enterprise data platforms (Databricks experience strongly
preferred).
• Design modular, maintainable, and upgradeable data pipelines.
• Implement Lakehouse architecture and enterprise-grade governance
standards.
• Enable ERP, AI systems, analytics platforms, and reporting tools to operate on
unified architecture.
• Ensure scalability, cost optimization, reliability, and security.
AI Models, Modern Architecture & Tooling
• Demonstrate strong understanding of AI/ML models, LLM architectures, and
latest AI frameworks.
• Build and integrate GenAI solutions using OpenAI SDK and modern AI
orchestration tools.
• Develop APIs and microservices using FastAPI and Pydantic for robust schema
validation.
• Architect modular, scalable, and future-ready systems.
• Maintain architectural vision ensuring maintainability, upgradeability, and
modularity.
• Leverage rapid prototyping (vibe tools) to quickly develop MVPs for client
validation and iteration.
Analytics & Visualization
• Build pricing dashboards and segmentation insights using Google Looker.
• Design business-facing analytical views aligned with executive reporting needs.
• Enable data-driven decision-making through interactive dashboards and BI
tools.
Governance, Compliance & Engineering Standards
• Ensure adherence to development standards, compliance requirements, and
enterprise guardrails.
• Define architecture review, code review, testing, and quality processes.
• Implement responsible AI practices and lifecycle governance.
• Maintain documentation, version control, and auditability standards.
Technical Leadership, Communication & Mentorship
• Serve as the on-site Technical Point of Contact.
• Mentor engineers, analysts, and interns; conduct structured knowledge transfer
sessions.
• Drive execution discipline and engineering excellence.
• Demonstrate excellent communication skills to collaborate with US-based
clients with limited timezone overlap.
• Communicate complex technical and pricing concepts clearly to technical
and non-technical stakeholders.
• Exhibit strong innovation mindset and proactive problem-solving attitude.
Requirements
• Bachelor's or Master's degree in Computer Science, Data Science, Economics,
Engineering, or related field.
• 8+ years of experience in Data Science, AI Engineering, Pricing Analytics, and
overall IT experience of 12+ years.
• Proven experience in pricing analytics, elasticity modeling, and customer
segmentation.
• Strong understanding of AI models, ML pipelines, and enterprise system
architecture.
• Strong business process understanding and ability to translate business goals
into technical systems.
• Advanced proficiency in Python, SQL, and ML frameworks.
• Experience with Pydantic, FastAPI, and API-based architectures.
• Experience integrating OpenAI SDK or similar LLM frameworks.
• Experience building dashboards using Google Looker or equivalent BI tools.
• Experience deploying production-grade ML/AI systems at enterprise scale.
• Strong communication and client-facing experience.
Strongly Preferred Qualifications
• Databricks and Lakehouse architecture experience.
• ERP integration experience (SAP preferred).
• Supply chain domain expertise.
• Experience in Time & Material enterprise engagements.
• Prior on-site leadership experience.
Benefits
As per company norms
