Data Science Architect

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. - Strong 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 opportunity to learn on one of the industry's largest digital learning platforms, with access to 250,000+ courses and numerous certifications. - We’re committed to ensure that people of all backgrounds feel encouraged and have a sense of belonging at Capgemini. You are valued for who you are, and you can bring your original self to work. - At Capgemini, you can work on cutting-edge projects in tech and engineering with industry leaders or create solutions to overcome societal and environmental challenges. - 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 make a difference everyday.