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.
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:
Robust 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.
Robust understanding of MLOps, CI/CD, model deployment, monitoring, and model governance.Experience with cloud platforms such as Azure, AWS, or GCP.
Knowledge of dist

📌 Data Science Architect Bengaluru
🏢 Capgemini Sogeti
📍 Bengaluru