Agile AI/ML Project Leader | Generative AI Solutions

Infosys Limited; Austin, Northern (TX, KY); Hybrid; USD 120,000 - 180,000; Full time

Benefits offered by this job

Disability Insurance

Health and Dependent Care Reimburse— (

Insurance (Accident/Critical Illness/H

401(k) Plan

Job summary

Infosys DNA unit is seeking a Data Science Consultant 2 to drive data analytics initiatives, develop predictive models, and deploy AI/ML solutions in Agile environments. You will collaborate with data scientists and engineers to deliver scalable analytics across business units.

You will guide model development, ensure data readiness, and contribute to governance and knowledge sharing while advancing cloud-based AI capabilities.

Qualifications

• Bachelor’s degree or foreign equivalent required.
• Experience managing AI/ML, analytics, data engineering, or digital transformation projects.
• Lead end-to-end delivery of AI/ML and Generative AI projects using Agile and Scrum methodologies.
• Collaborate with Data Scientists, ML Engineers, Data Engineers, Product Owners, and business stakeholders to define project roadmaps and priorities.
• Strong understanding of Generative AI, Machine Learning, MLOps, and Python development concepts.
• Experience with Agile tools such as Azure DevOps, Jira, or similar platforms.
• Knowledge of cloud platforms such as Azure, AWS, or GCP.
• Proven ability to manage cross-functional technical teams and multiple stakeholders.
• Strong communication, leadership, risk management, and problem-solving skills.

Responsibilities

• Develop data preparation tasks, while identifying patterns or anomalies.
• Ensure data readiness for advanced modeling.
• Develop models for complex use cases (e.g., forecasting models, LLM-based solutions), while refining algorithms to meet business needs, and ensure smooth deployment into scalable, production-ready solutions.
• Conduct testing and optimize algorithms for performance, reliability, and scalability, while providing guidance to team members in best practices.
• Design and develop predictive models and data-driven analyses to address business challenges.
• Build, evaluate, and deploy models, standardize code, and contribute to knowledge management.
• Leverage tools like SAS and R/Python to create reusable customizations for non-ML, ML, and deep learning algorithms, while enhancing analytics including LLMs, and create innovative, cost-effective solutions.
• Define analytics problems for projects; execute visualization, analysis, and predictive modeling under guidance.
• Proactively maintain models and implement improvements for accuracy and reliability.
• Apply governance controls to mitigate risks and ensure compliance.
• Analyze performance trends, recommend improvements, and document discrepancies for escalation.
• Maintain comprehensive documentation standards, while participating in knowledge transfer sessions.
• Participate in discussions with stakeholders to refine requirements, provide insights, and guide implementation of models.
• Apply the predefined quality measurement framework at an individual task level in the project.
• Deploy complex analytics tools or multi-system integration, while validating deployment success.
• Participate in developing scripts or templates for repeated deployments tasks.
• Contribute to analytic solutions, IP asset creation, and training initiatives.
• Contribute to thought leadership such as papers, innovative non-ML, ML, deep learning or LLM models, and proofs of concepts.
• Participate in and deliver analytics training, while contributing to content creation.
• Provide input for segment and unit-level business plans.

Skills

Agile PM

AI/ML Projects

Scrum

Stakeholder Collaboration

Gen AI / MLOps

Python Development

Cloud Platforms

Cross-functional Leadership

Communication Skills

Education

Bachelor’s degree or foreign equivalent

Tools

Azure DevOps

Jira

SAS

R/Python

MLflow

Azure ML

SageMaker

Kubeflow

Job description

Infosys DNA unit is seeking a Data Science Consultant 2 to drive data analytics initiatives, develop predictive models, and deploy AI/ML solutions in Agile environments. You will collaborate with data scientists and engineers to deliver scalable analytics across business units.

You will guide model development, ensure data readiness, and contribute to governance and knowledge sharing while advancing cloud-based AI capabilities.