Data Science Architect

Experience: 14–17 Years

Grade: D2

Location: Bangalore

Job Description

We are looking for an experienced Data Science Architect to lead the design and implementation of enterprise-scale AI, Machine Learning, and advanced analytics solutions. The ideal candidate should have strong expertise in Machine Learning, LLMs, MLOps, Deep Learning, and Cloud platforms, along with experience in architecting scalable and secure data science solutions.

The role involves providing technical leadership to Data Scientists, ML Engineers, and Analytics teams while working closely with business, technology, product, and data engineering stakeholders.

Key Responsibilities

• Design scalable, secure, and high-performance Data Science and Machine Learning architectures for advanced analytics and AI-driven solutions.
• Lead the design and implementation of end-to-end analytical solutions, including data acquisition, feature engineering, model development, deployment, and monitoring.
• Define standards, frameworks, and best practices for Data Science, Machine Learning, MLOps, AI development, and Model Governance.
• Translate business challenges into scalable AI and Data Science solutions in collaboration with business, product, technology, and analytics teams.
• Design solutions for predictive analytics, forecasting, optimization, recommendation systems, NLP, Computer Vision, and Deep Learning.
• Lead the development and deployment of Machine Learning models, ensuring scalability, reliability, explainability, and operational efficiency.
• Establish and manage the complete ML model lifecycle, including experimentation, versioning, validation, deployment, monitoring, and continuous improvement.
• Drive the adoption of LLM and Generative AI capabilities across relevant business use cases.
• Establish and implement MLOps, CI/CD, model monitoring, and model governance practices.
• Ensure adherence to Responsible AI principles, including fairness, transparency, explainability, privacy, security, and compliance.
• Collaborate with Data Engineering and Enterprise Architecture teams to build integrated data ecosystems supporting AI and advanced analytics workloads.
• Evaluate emerging AI, ML, and data technologies and recommend solutions aligned with business requirements.
• Mentor Data Scientists, ML Engineers, and Analytics teams and provide technical leadership.
• Present complex analytical concepts and recommendations clearly to senior business and technology stakeholders.
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Required Skills & Qualifications

• Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, Data Science, or a related discipline.
• 14–17 years of experience in Data Science, Machine Learning, AI, or Advanced Analytics.
• Strong experience in Data Science / AI-ML Architecture and enterprise-scale solution design.
• Strong expertise in Machine Learning, Predictive Modeling, Statistics, and Advanced Analytics.
• Hands-on experience with LLMs / Large Language Models and Generative AI.
• Strong understanding and practical experience in MLOps.
• Experience with Deep Learning, NLP, and Computer Vision.
• Strong proficiency in Python; working knowledge of R and SQL.
• Experience with at least one major cloud platform: AWS, Azure, or GCP.
• Strong understanding of CI/CD, model deployment, monitoring, versioning, and model lifecycle management.
• Experience with Data Governance, Model Governance, Data Quality, Security, Privacy, and Responsible AI.
• Knowledge of distributed computing and big data technologies such as Spark, Hadoop, or equivalent platforms.
• Experience designing and delivering enterprise-scale AI, ML, and Data Science solutions.
• Strong analytical, problem-solving, consulting, communication, and stakeholder-management skills.
• Proven experience mentoring and providing technical leadership to Data Science and ML teams.