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Capgemini

Global consulting, technology services, outsourcing

Data Science Architect

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeBengaluru, Karnataka, IndiaNo salary listedIn-person

About the Job

Requirements

  • 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 deep learning, natural language processing, 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.
  • Experience architecting and delivering enterprise-scale AI, analytics, and data science solutions across multiple business domains.

Responsibilities

  • 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, natural language processing, 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.

About the Company

Capgemini

Global consulting, technology services, outsourcing

Capgemini provides consulting, technology services, and outsourcing to help organizations transform digitally. Its offerings include strategy and transformation consulting, system integration, application development, IT infrastructure management, and managed IT operations. It differentiates itself with a global presence in over 50 countries and a focus on applying AI, cloud, and cybersecurity to real business problems. Its goal is to help clients navigate digital transformation and improve efficiency and innovation through tailored, contract-based or managed services.

Company size
10,001+
Company stage
IPO
Headquarters
Paris, France
Founded
1967

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