Technical Project Manager - AI/ML Ops (ONSITE)

Technical Project Manager - AI/ML Ops

This is an onsite role and can be performed from any of the following locations: Dallas, TX; Atlanta, GA; or Charlotte, NC.

The Technical Project Manager for Analytics plays a strategic role in overseeing and delivering analytics and AI/ML Ops projects. This position requires extensive project management experience, particularly in Data Science, Data Engineering, and Model Operations. The manager leads the management of business use cases of AIML Models and GenAI applications, ensuring alignment with organizational goals and technical standards.

Key Responsibilities

• Project Management: Lead analytics projects with a focus on Data Science, Data Engineering, and AI/ML Ops. Oversee Model Ops and maintain accountability for all project related deliverables.
• Business Use Case Maintenance and Monitoring utilizing design thinking methodologies. Facilitate workshops to elicit business requirements and scenarios.
• Data Science & Engineering: Possess a solid understanding of statistical modelling frameworks and machine learning applications. Maintain data pipelines for AI/ML models with proficiency in tools such as Kubernetes, Docker, Apache Airflow, and the ELK stack.
• Technical Skills: Demonstrate hands-on expertise in SQL and Python for data analysis and engineering tasks.
• Agile Delivery: Implement Agile methodologies within the team, leading Agile cadence meetings and fostering an adaptive delivery environment.
• Documentation: Prepare detailed Business Requirements Documents (BRD) and technical specifications. Create and maintain flow diagrams, sequence diagrams, class diagrams, and deployment diagrams to support solution clarity and communication.
• Stakeholder Communication: Exhibit strong communication and articulation skills to bridge technical and non-technical stakeholders.
• Sector Experience: Experience in Banking and Financial Services (BFS) is highly desirable.
• Solution Design: Design solutions for Model Ops and demonstrate familiarity with model ops tools such as MLFlow or DataRobot.
• Flexibility: Adapt to dynamic environments and maintain flexible working hours to meet project demands.

Required Skills and Experience

• Proven track record in delivering analytics products and predictive analytics use-cases.
• Experience in setting up frameworks and introducing Agile Delivery Methodologies.
• Strong background in Data Science and Data Engineering.
• Proficiency in SQL, Python, Apache Airflow, and ELK stack.
• Experience working in a matrix organization, leading teams of more than five members.
• Client management and product management, including roadmap strategy and delivery planning.
• At least 10 years of experience in Technical Product Management with a focus on Agile delivery.

Preferred Skills

• Exposure to Azure cloud services.
• Ability to thrive in a fast-paced environment.

Cognizant will only consider applicants for this position who are legally authorized to work in the United States without requiring company sponsorship now or at any time in the future.