Data Science Manager

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

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

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

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

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

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

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• High-ownership role with direct exposure to diverse industries and cutting-edge AI problems.
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• Opportunity to lead delivery and shape solutions from presales through production.
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• A collaborative team working at the intersection of OR, ML, and GenAI.
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To apply, please share your CV and a brief note on a data science project you led end-to-end.