Data Architect (AI/ML)

Job Description (Summary)

The Data Architect (AI/ML) plays a critical role in delivering advanced AI solutions that help businesses achieve their objectives and foster innovation. The ideal candidate should have a deep understanding of machine learning, deep learning, natural language processing (NLP), computer vision, chatbots, and generative AI (GEN-AI) and be able to apply these skills to enhance various business outcomes. As part of the data architecture team, the Data Architect (AI/ML) will be instrumental in shaping the organization's AI strategy and showcasing the potential of AI through early-stage solutions. The ideal candidate must possess strong analytical and problem-solving skills, as well as excellent communication and interpersonal skills, to collaborate effectively with stakeholders across the organization. This role requires a creative and innovative mindset to adapt to emerging trends and technologies in AI/ML, along with a passion for delivering impactful AI solutions that make a tangible difference in the real world.

Duties and Responsibilities:

• Develop and implement machine learning algorithms and models.
• Design and implement AI solutions that enhance business outcomes.
• Train and optimize models using large datasets.
• Develop and deploy machine learning models that leverage large datasets.
• Develop data pipelines and data processing workflows.
• Apply NLP and computer vision techniques to extract insights from unstructured clinical/healthcare data.
• Perform data analysis and data visualization to deliver data-driven insights.
• Define best practices for Deploying AI models to production environments using MLOps.
• Build chatbots that improve customer engagement and satisfaction.
• Use Generative AI (GEN-AI) to generate new ideas and solutions.
• Collaborate with cross-functional teams to integrate AI solutions into products and services.
• Strong hands-on experience in Python and polular libraries like Scikit-learn, Tensorflow, Keras, PyTorch and pandas.
• Staying current with the latest advancements in AI, ML, and machine learning.
• Providing technical guidance and support to Data Engineers, Business users, and software application team members
• Maintaining documentation and ensuring compliance with relevant AI governance, regulations, and standards.
• Ensure end-to-end AI model governance and explainability.
• Expert knowledge of Business intelligence (BI), Dashboards and Analytics tools.
• Communicate effectively with both technical and non-technical stakeholders.
• Participate in proof of concepts, analysis/design, assessing new technologies, identifying data trends, and performing complex data analysis and analytics using AI and ML.
• Collaborate with cross-functional teams, including business stakeholders, data scientists, data engineers, and IT teams, to define future data management architecture, aligning with value creation opportunities across the business.
• Define design patterns for MLOps, AI/ML best practices.
• Experience with workflow management systems like Apache Airflow, Orkes and AWS Step Functions can be useful for orchestrating complex data workflows and pipelines.
• Experience utilizing API development and integration using tools such as MuleSoft and REST APIs