Principal Data Scientist

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• Lead the design and deployment of predictive and generative AI models that power personalization, pricing, search, and optimization in manufacturing domains.
• Collaborate with product leaders to align ML initiatives with strategic business goals and drive product innovation through data-driven experimentation and modelling.
• Architect scalable ML infrastructure and automated workflows using cloud-native tools (e.g., AWS, EC2, Kubernetes) to support efficient model training, deployment, and analytics across diverse datasets.
• Ensure long-term performance and compliance of production AI models though robust governance and monitoring.
• Provide technical leadership and mentorship to data scientists, shaping an innovative team culture and fostering high-performance and continuous learning.
• Serve as a cross-functional technical leader, shaping company-wide technical initiatives beyond data science. Partner with engineering, product, and platform teams to influence architecture, innovation agendas, and technical standards across the organization.
• Act as a senior technical advisor, leading resolution of complex modelling issues and acting as the escalation point for critical incidents.
• Lead the exploration and strategic application of GenAI, identifying high-impact use cases and guiding their integration across products and platforms.

Required

• Advanced academic credentials in a quantitative field such as Computer Science, Engineering, Mathematics, or related discipline
• 8+ years of experience in data science, machine learning, or applied AI, with a strong portfolio of high-impact projects in production
• Expert-level programming skills in Python and SQL, and fluency with leading ML/AI frameworks (e.g., scikit-learn, TensorFlow, PyTorch)
• Direct experience with GenAI/LLM technologies, including tools like Hugging Face, LangChain, OpenAI APIs, vector databases, and fine-tuning methods
• Deep knowledge of machine learning algorithms (supervised, unsupervised, deep learning), including model evaluation, explainability, and selection for business-critical use cases
• Strong hands-on experience with cloud infrastructure (AWS), containerization (Docker), and orchestration (Jenkins, Airflow)
• Proven capability in MLOps, including CI/CD pipelines, model monitoring, versioning, and automated retraining
• Hands of experience with design and analysis of A/B and multivariate experiments to measure the impact of product changes and business strategies with statistical rigor
• Experience working with cloud environments like AWS and leveraging its offerings such as Lambda Bedrock, SageMaker, etc
• Experience deploying and serving models through APIs (e.g., Flask, FastAPI) in both real-time and batch-processing environments
• Excellent communication and stakeholder management skills, able to translate complex concepts into actionable insights for non-technical audiences
• Demonstrated success mentoring teams, guiding technical strategy, and advocating for best practices in experimentation, reproducibility, and ethical AI
• Experience working in agile product development environments (Scrum/Kanban); experience influencing product roadmaps is a strong plus

Preferred

• Hands-on expertise in AI and LLM development with Finetuning expertise in a real-world business environment
• Experience deploying AI models for real-time applications in manufacturing domain
• Strong knowledge base of MLOps practices for efficient model deployment and scaling
• Proven leadership and mentorship experience, with a passion for developing and inspiring high-performing teams
• Contributions to open-source AI/ML projects, publications, or presentations at industry conferences
• Design and manage reusable and consistent feature stores to improve model development efficiency.
• Use DVC (Data Version Control) for experiment tracking and data lineage alongside Git.
• Design and implement event-triggered systems (e.g., via AWS Lambda triggers) for ML operations.
• Integrate ML models into serverless computing workflows for lightweight, on-demand inference.

Personal
Besides the professional qualifications of the candidates we place great importance in addition to various forms personality profile. These include:

• High analytical skills
• A high degree of initiative and flexibility
• High customer orientation
• High quality awareness
• Excellent verbal and written communication skills

About Infosys
Infosys is a global leader in next-generation digital services and consulting. We enable clients in 46 countries to navigate their digital transformation. With over three decades of experience in managing the systems and workings of global enterprises, we expertly steer our clients through the many next of their digital journey. We do it by enabling the enterprise with an AI-powered core that helps prioritize the execution of change. We also empower the business with agile digital at scale to deliver unprecedented levels of performance and customer delight. Our always-on learning agenda drives their continuous improvement through building and transferring digital skills, expertise and ideas from our innovation ecosystem.
Visit https://www.infosys.com to see how Infosys can help your enterprise navigate your next.

All aspects of employment at Infosys are based on merit, competence and performance. We are committed to embracing diversity and creating an inclusive environment for all employees. Infosys is proud to be an equal opportunity employer