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.
To apply, please share your CV and a brief note on a data science project you led end-to-end.
