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.
