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Job Description Summary -Level 4: Data Scientist 1 Location: Hyderabad | About the Position The AI and Data Science Operations (BSI) team at Novartis is committed to enhancing decision-making by leveraging advanced AI technologies to deliver actionable insights that improve performance and productivity. We work closely with international business units to generate innovative ideas and data-driven insights, enabling informed strategic decisions. This role will be contributing to the development and execution of a multi-year AI strategy and roadmap aimed at optimizing operational efficiency and driving organizational growth. By staying at the forefront of advancements in generative AI and large language models (LLMs), the Agentic AI engineer ensures and execute cutting-edge technologies. As a key member of the AI and DS BSI team, you will design, pilot, and scale AI solutions with more focus on GenAI and Agentic AI aligned with the broader International AI strategy, transforming business processes and outcomes. Job Description Location: Hyderabad Key Responsibilities Develop and deploy of scalable AI solutions, focusing on GenAI applications. Drive innovation by staying current with advancements in AI, particularly generative models and LLM technologies. Collaborate with a high-performing team of data scientists, ensuring alignment within AI and Data Science initiatives. Engage in hands-on development and guide best practices for code quality, version control, and ML/AI Ops pipelines. Collaborate with cross-functional teams to integrate AI-driven solutions across platforms and services. Champion a culture of experimentation and adoption of best practices, inspiring teams with a can-do attitude and acting as an AI role model. Minimum Requirements Education: Bachelors degree in a related field with 10-12 years of experience, or Masters degree with 8-10 years of relevant experience. Certifications in GenAI/ML platforms (AWS/Azure) are a plus. Experience Minimum 7 years working in advance data science projects, including 2-3 years leading high-performing data science or ML teams from problem framing. Experience delivering GenAI and agentic solution and proven ability to build and deploy scalable ML models using cloud services (AWS, Azure). Technical Expertise Deep understanding of autonomous AI agents and frameworks such as LangGraph, LangFuse, Chain of Thought (CoT), and ReACT. Strong background in Retrieval-Augmented Generation (RAG) and knowledge grounding techniques Strong knowledge of LLMs, classical ML/DL algorithms, time series analysis, and core statistical methods. Proficiency in Python and hands-on experience deploying models in production environments. Business Acumen Ability to translate complex algorithmic outputs into clear, outcome-oriented narratives for senior leadership. Preferred Requirements Experience in the commercial pharma industry. Masters in computer science or data science. Familiarity with Agile methodologies for project delivery. Ability to balance operational execution with strategic thinking. Strong collaboration skills with cross-functional teams. Excellent communication skills for engaging senior leadership. Required Skills Large Language Models (LLMs) Agentic AI Frameworks Machine Learning Model Deployment AWS/Azure Cloud Services Deep Learning & Foundation Models Statistical Analysis & Reporting Python Programming Problem Solving Why Novartis:Helping people with disease and their families takes more than innovative science. It takes a community of smart, passionate people like you. Collaborating, supporting, and inspiring each other. Combining to achieve breakthroughs that change patients lives. Ready to create a brighter future together. https://www.novartis.com/about/roadmap/people-and-culture Commitment to Diversity & Inclusion: Novartis is committed to building an outstanding, inclusive work environment and diverse teams representative of the patients and communities we serve. Values and Behaviors: Demonstrates and upholds Novartis values and behaviors in all aspects of work and collaboration. Location: Hyderabad NKC. Hybrid | 3 days a week in office is mandatory. Skills Desired AI Agents, AI Agents, AI Systems, Artificial Intelligence (AI), Biostatistics, Change Management, Curious Mindset, Data Governance, Data Literacy, Data Quality, Data Science, Data Visualization, Deep Learning, Generative AI, Generative AI Agents, Large Language Models (LLMs), Learning Agility, Logistic Regression Model, Machine Learning (ML), Machine Learning Algorithms, Multiagent Systems, Natural Language Processing (NLP), Pandas (Python), python, Python (Programming Language) {+ 4 more} .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.