Your Role

- Design scalable, secure, and high-performance data science and machine learning architectures to support advanced analytics and AI-driven decision-making.
- Lead the architecture and implementation of end-to-end analytical solutions, from data acquisition and feature engineering to model deployment and monitoring.
- Establish standards, frameworks, and best practices for data science, machine learning, MLOps, model governance, and AI solution development.
- Collaborate with business, product, technology, and analytics stakeholders to identify opportunities and translate business challenges into data science solutions.
- Define architectures for predictive analytics, forecasting, optimization, recommendation systems, NLP, computer vision, and other advanced analytical applications.
- Oversee the development and deployment of machine learning models, ensuring scalability, reliability, explainability, and operational excellence.
- Establish model lifecycle management processes, including experimentation, versioning, validation, deployment, monitoring, and continuous improvement.
- Ensure adherence to Responsible AI principles, including fairness, transparency, explainability, privacy, security, and regulatory compliance.
- Partner with Data Engineering and Enterprise Architecture teams to design integrated data ecosystems that support AI and advanced analytics workloads.
- Evaluate and recommend emerging technologies, tools, and industry best practices to enhance organizational AI and data science capabilities.
- Mentor and provide technical leadership to Data Scientists, ML Engineers,



and Analytics teams while fostering innovation and knowledge sharing.

Your Profile

- Strong expertise in Statistics, Machine Learning, Predictive Modeling, and Advanced Analytics.Proficiency in Python, R, SQL, and leading data science libraries and frameworks.
- Experience with Machine Learning, Deep Learning, NLP, Time Series Forecasting, and Optimization techniques.
- Solid understanding of MLOps, CI/CD, model deployment, monitoring, and model governance.Experience with cloud platforms such as Azure, AWS, or GCP.
- Knowledge of distributed computing and big data technologies such as Spark, Hadoop, or equivalent platforms.
- Expertise in data visualization, storytelling, and communicating complex analytical concepts to business stakeholders.
- Strong understanding of data governance, data quality, security, privacy, and Responsible AI principles. Excellent leadership, stakeholder management, problem-solving, and consulting skills.
- Experience architecting and delivering enterprise-scale AI, analytics, and data science solutions across multiple business domains.

What will you love working at Capgemini

- You will have the on one of the industry''s largest digital learning platforms, with access to 250,000+ courses and numerous certifications.
- Were committed to ensure that people of all backgrounds feel encouraged and have a sense of belonging at Capgemini. .
- - Capgemini office campuses in India are green and run on 100% renewable electricity. We have installed Solar plants across India locations and Battery Energy Storage Solution(BESS) in the Noida and Mumbai campuses. You will have chance to everyday.

📌 Data Science Architect (Bengaluru)
🏢 Capgemini
📍 Bengaluru