Data Science Architect

Capgemini; Bengaluru; On-site; INR 4,000,000 - 7,000,000; Full time

Benefits offered by this job

Learning platform access

Belonging and inclusion initiatives

Renewable energy campuses

Job summary

Capgemini is seeking a senior data science leader to design scalable, secure analytics architectures and lead end-to-end ML solutions. You will define standards for MLOps, governance, and AI development while collaborating with business, product, and tech stakeholders to translate challenges into innovative data-driven outcomes.

responsible for overseeing model deployment, lifecycle management, and adherence to Responsible AI principles in a complex enterprise environment.

Qualifications

• Extensive experience in data science, ML, and analytics architectures.
• Experience with ML, DL, NLP, forecasting, optimization.
• Strong CI/CD, MLOps, model deployment and governance knowledge.
• Experience with cloud platforms such as Azure, AWS, or GCP.
• Knowledge of distributed computing (Spark/Hadoop).
• Experience communicating with stakeholders and leadership.

Responsibilities

• Design scalable data science architectures and ML systems for analytics.
• Lead end-to-end analytics solutions from data acquisition to deployment.
• Establish standards for MLOps, governance, and AI solution development.
• Collaborate with business, product, technology, and analytics stakeholders.
• Define architectures for predictive analytics, forecasting, NLP, CV, and analytics apps.
• Oversee development and deployment of ML models with reliability and explainability.
• Establish model lifecycle management: experimentation, versioning, deployment, monitoring, improvement.
• Ensure Responsible AI: fairness, transparency, privacy, security, regulatory compliance.
• Partner with Data Engineering and Enterprise Architecture teams to build integrated data ecosystems.
• Evaluate emerging technologies and best practices to advance AI capabilities.
• Mentor Data Scientists and ML Engineers to foster innovation.

Skills

Statistics

Machine Learning

Predictive Modeling

Python

R

SQL

NLP

Cloud Platforms

ML Ops

Big Data

Model Governance

Tools

Spark

Hadoop

Job description

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 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.