Data Science Manager

ORMAE; Bengaluru; Hybrid; INR 4,500,000 - 7,500,000; Full time

Job summary

ORMAE in Bangalore, India, is seeking a Data Science Manager to lead technical delivery and client engagements with a strong emphasis on presales and solution design. The role blends hands-on data science work with leadership and stakeholder engagement across pharma, FMCG, healthcare, and more.

The ideal candidate will architect scalable analytics solutions, guide a team of data scientists, and translate business problems into deployable AI products, while staying current with advances in ML,

Qualifications

• 8+ years in data science / applied ML with delivery experience.
• 2+ years leading projects or mentoring a team.
• Strong quantitative background from a relevant degree.
• Hands-on with modern AI including LLMs, GenAI, and orchestration.
• Proficient in Python and SQL; cloud & containerization experience.

Responsibilities

• Own end-to-end delivery of multiple client projects from problem framing to deployment.
• Architect data science solutions across forecasting, NLP/LLM, and optimization use cases.
• Lead and mentor a data science team; ensure code quality and reproducibility.
• Engage in presales, shape tailored solution proposals, and present proofs-of-concept.

Skills

Team leadership

Presales aptitude

Client-facing communication

Data science / ML

Problem framing & data strategy

Education

Quantitative degree (Statistics, CS, Math, OR)

Tools

Python

SQL

Docker

Kubernetes

Flask/FastAPI

MLflow

Azure/AWS

Databricks

Job description

Data Science Manager

ORMAE · Bangalore, India · Full-time · Data Science / AI Consulting

ABOUT THE ROLE

ORMAE is an AI, Optimization, and Machine Learning consulting firm delivering high-impact data science solutions across pharma, FMCG, healthcare, aerospace, manufacturing, e-commerce, and hospitality. We are looking for a Data Science Manager who can lead the technical delivery of client engagements end-to-end while actively supporting presales and solutioning to help win new business.

This is a hybrid technical-and-client-facing role: roughly 60-70% hands-on and delivery leadership, 30-40% presales, solution design, and stakeholder engagement. The ideal candidate is a strong data scientist who can architect solutions, guide a team, and translate business problems into deployable analytics and AI products.

KEY RESPONSIBILITIES

Technical Delivery & Leadership

• Own the end-to-end delivery of multiple concurrent client projects - from problem framing and data strategy through modeling, deployment, and handover.
• Architect and review data science solutions across forecasting, optimization, recommendation, predictive maintenance, NLP/LLM, and agentic AI use cases.
• Lead, mentor, and technically guide a team of data scientists; set standards for code quality, model validation, and reproducibility.
• Ensure solutions are production-ready - scalable, well-documented, and deployable in diverse client environments.
• Manage client expectations, timelines, and deliverables, acting as the primary technical point of contact for engagements.

Presales & Solutioning

• Partner with the business development and presales teams to scope opportunities, understand client needs, and shape tailored solution proposals.
• Contribute to proposals, solution architectures, effort estimates, and technical responses to RFPs.
• Design and present proofs-of-concept, demos, and solution walkthroughs to prospective clients.
• Translate ambiguous business problems into clear, feasible analytics/AI approaches that map to measurable client value.

Innovation & Capability Building

• Contribute to reusable accelerators, frameworks, and IP that speed up delivery and strengthen ORMAE's solution offerings.
• Stay current with advances in ML, GenAI, agentic systems, and optimization, and bring relevant techniques into client work.

REQUIRED SKILLS & EXPERIENCE

• Experience: 8+ years in data science / applied ML, including 2+ years leading projects or mentoring a team.
• Education: Strong quantitative background - degree in Statistics, Computer Science, Mathematics, Operations Research, or a related field.
• Core ML/Stats: Regression, classification, clustering, time-series forecasting, optimization, and statistical inference, with sound grasp of model validation.
• Modern AI: Hands-on experience with LLMs, RAG, and GenAI; exposure to agentic AI / MCP-based orchestration is a strong plus.
• Engineering: Proficient in Python and SQL; experience with cloud (Azure/AWS), containerization (Docker/Kubernetes), and deployment frameworks (Flask/FastAPI, MLflow).
• Delivery: Track record of taking models from prototype to production in real client or business environments.
• Communication: Excellent written and verbal communication; able to present technical concepts to non-technical business stakeholders.
• Presales aptitude: Comfort in client-facing settings - scoping, solutioning, and supporting business development.

GOOD TO HAVE

• Prior experience in a consulting or client-services environment with multiple concurrent engagements.
• Domain exposure to one or more of: pharma, FMCG, healthcare, aerospace, manufacturing, e-commerce, or hospitality.
• Experience contributing to proposals, RFPs, or productized accelerators.
• Familiarity with BI/visualization (Power BI) and big-data tooling (PySpark, Databricks, Kafka).

WHAT WE OFFER

• High-ownership role with direct exposure to diverse industries and cutting-edge AI problems.
• Opportunity to lead delivery and shape solutions from presales through production.
• A collaborative team working at the intersection of OR, ML, and GenAI.