Role : Data Scientist

Location : Koregaon Park, Pune Hybrid Working : 3 days in office CET Timezone

Experience : 25 years

Project context

As a Data Scientist, you will design experiments and productionize machine learning and generative AI capabilities on Azure, focusing on measurable business outcomes, reproducibility, and MLOps best practices. You will collaborate directly with stakeholders, guide technical decisions, and help shape patterns and standards for agentic AI within the enterprise.

This role will focus on SyGrow. SyGrow is sales copilot initiative. In this role, you will turn sales and stakeholder needs into data productsexploring new features, validating hypotheses, and shipping ML- and LLM-powered capabilities that drive commercial impact. You balance fast iteration with enterprise-grade practices in data, MLOps, and Responsible AI.

Key Responsibilities :

- Explore and prototype new SyGrow features from hypotheses to validated experiments with measurable outcomes.

- Translate sales and stakeholder needs into analytical problems, KPIs, and success criteria.

- Build, evaluate, and iterate ML models for recommendations, scoring, forecasting, and insights. Implement robust data ingestion, feature engineering, and training pipelines in Azure ML and Microsoft Fabric.

- Productionize models with CI/CD, versioning, telemetry, and rollback using Azure DevOps. Leverage LLMs (prompting, RAG) to augment the sales copilot; define guardrails and evaluation strategies.

- Ensure privacy, security, and compliance across data and model lifecycles.

- Monitor performance, drift, and cost; run A/B tests and incorporate user feedback. Collaborate with engineering and product to ship incremental value in agile sprints. Document decisions, share knowledge, and contribute reusable components and templates.

- Integrate with CRM/BI workflows and data sources to operationalize outcomes.

- Mentor interns/juniors and champion best practices in Data Science and MLOps.

Specific Knowledge/Experience :

- Education : Masters in Data Science, Computer Science, Engineering, Mathematics, or related field or equivalent practical experience.

- Experience : 25 years hands-on experience delivering ML/DS solutions from exploration to production.

- Partnered with business stakeholders (preferably sales/commercial).

- Worked in agile teams. Big plus : Implemented MLOps on Azure Technical Knowledge : Python, Pandas, scikit-learn, EDA Excellent foundations of statistics, machine Learning algorithms and techniques Prompt engineering, RAG data engineering fundamentals (SQL/ETL/APIs);

- Experience with some of following will be a big plus : Azure Machine Learning; Azure OpenAI / Azure AI Foundry; Azure AI Search; Azure Data Factory; Azure DevOps; Microsoft Fabric; monitoring and cost governance.

- Skills and behavioral competencies : Startup mindset & ownership : proactive, autonomous, resourceful, bias for action.

- Business impact orientation : frames problems, defines KPIs, measures value, iterates quickly. Collaboration & knowledge sharing : partners across Sales, Product, Engineering; contributes reusable assets.

- Communication : explains complex topics clearly to non-technical stakeholders, team player Curiosity & craftsmanship : keeps pace with ML/LLM advances; adopts what works; attention to detail

- Responsible AI : builds with security, privacy, and compliance by design. Strong programming discipline : testing, code reviews, documentation, CI/CD.

Whats in it for the candidate :

Be part of and contribute to a once-in-a-lifetime change journey Willing to be part of a team that is going to tackle big bets Have a fun and work at a high pace Be part of a forward-thinking company committed to innovation and excellence.

Work in a collaborative and inclusive environment that values diverse perspectives. Contribute to actions that have a meaningful impact on advancing humanity. If you are passionate about data engineering and eager to make a difference