Data Science Architect

Join a team driving enterprise-wide AI, advanced analytics, and data-driven transformation initiatives. As a Data Science Architect, you will lead the design and implementation of scalable data science and machine learning platforms that enable intelligent decision-making, predictive insights, and business innovation. You will collaborate with business leaders, data engineers, data scientists, and technology teams to build next-generation AI and analytics solutions. Your Role You will be responsible for defining and delivering enterprise-scale data science and machine learning architectures, ensuring that AI and analytics solutions are scalable, secure, reliable, and aligned with business objectives. As a technical leader, you will establish best practices for data science, MLOps, model governance, and Responsible AI while driving innovation across the organization. In this role, you will: 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. Define enterprise standards, frameworks, and best practices for Data Science, Machine Learning, MLOps, and AI solution development. Collaborate with business, product, technology, and analytics stakeholders to translate business challenges into data-driven solutions. Architect advanced analytics solutions including predictive modeling, forecasting, optimization, recommendation engines, NLP, and computer vision applications. Oversee the development, deployment, and operationalization of machine learning models, ensuring scalability, reliability, and performance. Establish model lifecycle management processes including experimentation, versioning, validation, deployment, monitoring, and continuous improvement. Implement model governance frameworks that promote transparency, explainability, compliance, and operational excellence. Partner with Data Engineering and Enterprise Architecture teams to build integrated data ecosystems supporting AI and analytics workloads. Evaluate emerging technologies, tools, and industry trends to strengthen organizational AI and advanced analytics capabilities. Drive adoption of Responsible AI principles, including fairness, privacy, security, and regulatory compliance. Mentor and provide technical leadership to Data Scientists, ML Engineers, and Analytics teams, fostering innovation and knowledge sharing. Your Profile Mandatory Skills 14–17 years of experience in Data Science, Advanced Analytics, Machine Learning, and AI solution architecture. Strong expertise in Statistics, Machine Learning, Predictive Modeling, and Advanced Analytics techniques. Proficiency in Python, R, SQL, and leading Data Science libraries and frameworks. Extensive experience with Machine Learning, Deep Learning, Natural Language Processing (NLP), Time Series Forecasting, and Optimization techniques. Strong understanding of MLOps, CI/CD pipelines, model deployment, monitoring, and model governance frameworks. Experience designing and delivering enterprise-scale AI, Analytics, and Data Science solutions. Hands-on experience with cloud platforms such as Azure, AWS, or Google Cloud Platform (GCP). Knowledge of distributed computing and big data technologies including Spark, Hadoop, or equivalent platforms. Experience building scalable data platforms and AI-driven analytical solutions. Expertise in data visualization, storytelling, and translating complex analytical insights into business outcomes. Strong understanding of data governance, data quality, privacy, security, and Responsible AI principles. Excellent leadership, consulting, stakeholder management, and problem-solving skills. Preferred Skills Experience with Generative AI, Large Language Models (LLMs), and AI-powered analytics solutions. Exposure to modern AI frameworks, vector databases, and Retrieval-Augmented Generation (RAG) architectures. Knowledge of cloud-native AI and analytics platforms such as Databricks, Azure Synapse, Microsoft Fabric, or similar technologies. Experience working across multiple business domains and enterprise transformation programs. Relevant certifications in Data Science, Cloud, AI/ML, or Enterprise Architecture. What You'll Love About Working Here Opportunity to architect and deliver large-scale AI, Machine Learning, and Advanced Analytics solutions. Work with cutting-edge technologies across AI, Data Science, Cloud, and Big Data ecosystems. Collaborative environment with architects, data scientists, engineers, and business leaders. Continuous learning through innovation-led projects and emerging AI technologies. Flexible work environment that encourages technical excellence, leadership, and professional growth.