Sr Data Scientist

Overview

Senior Data Scientist on Baxter's Enterprise Data Analytics team, leading end-to-end advanced analytics, machine learning, Generative AI and Agentic AI solutions across multiple business domains.

What you'll do

• Lead the end-to-end lifecycle of advanced analytics, machine learning, Generative AI, and Agentic AI solutions, from opportunity identification and experimentation through production deployment, monitoring, and continuous improvement.
• Translate ambiguous business problems into well-defined data science hypotheses, solution designs, success metrics, and scalable implementation roadmaps.
• Develop and maintain advanced predictive and forecasting models for sales, revenue, expense management, and cash-flow forecasting.
• Design, architect, train, and deploy advanced machine-learning frameworks and traditional time-series models to improve forecast accuracy for sales, revenue, operating expenses, and cash flow.
• Own model validation, explainability, reliability, documentation, monitoring, and governance in line with responsible AI and regulatory expectations.
• Provide technical leadership through architecture reviews, code reviews, mentoring, standards definition, and hands-on resolution of complex analytical challenges.
• Communicate analytical findings, business implications, risks, and recommendations clearly to senior leaders and non-technical stakeholders.
• Explore emerging AI technologies and adopt solutions that deliver business value.

What you'll need

• Bachelor's or Master's degree in computer science, Data Science, Information Technology, or a related technical discipline.
• Minimum 8 years of progressive experience in data science, machine learning, or applied AI, including experience leading complex enterprise initiatives.
• Strong hands-on record of designing, developing, and deploying production-grade machine learning, Generative AI, or Agentic AI solutions.
• Experience working with large, complex, and distributed datasets in enterprise environments.
• Advanced proficiency in Python, SQL, and PySpark, with strong expertise in libraries such as pandas, NumPy, scikit-learn, and NLP libraries.
• Machine learning and statistics: regression, classification, clustering, forecasting, time-series analysis, experimentation, optimization, ensemble methods, and model evaluation.
• Deep learning and Generative AI: hands-on experience with PyTorch or TensorFlow, LLM application patterns, retrieval-augmented generation, prompt engineering, model fine-tuning, evaluation, guardrails, and agentic workflows.
• Hands-on experience building autonomous AI agents and implementing the Model Context Protocol (MCP) or comparable tool-integration patterns.
• Strong hands-on experience with AWS machine-learning services, including Amazon SageMaker and Amazon Bedrock.
• Experience packaging, deploying, monitoring, and maintaining production models and AI services using APIs, containers, model registries, automated testing, observability, and retraining workflows.
• Experience applying data science and AI across Finance, FinTech, Sales, Supply Chain, and Healthcare; ability to transfer methods and insights across domains is essential.
• Ability to explain complex machine-learning outputs, financial drivers, and business implications to cross-functional teams and stakeholders without black-box ambiguity.

Nice to have

• Experience in healthcare, commercial, supply chain, or financial analytics environments.
• Good understanding of statistical forecasting methodologies, time-series analysis, and error metric evaluations.
• Experience working in Agile delivery models and contributing to product-oriented data science teams.
• Strong business acumen and the ability to translate technical concepts into clear decisions, trade-offs, and outcomes for non-technical stakeholders.
• An industry-recognized professional certification in data science or AI, or completion of a top-tier data science executive program.

Details

• Location: Gurgaon, Haryana.