Description

Job Responsibilities include:

Lead and manage enterprise AI/ML, data science, and analytics initiatives from concept through production deployment, ensuring delivery of scalable business solutions.

Architect and oversee data pipelines, machine learning workflows, and big data processing platforms using AWS, Databricks, Spark, and cloud-native technologies.

Drive MLOps best practices, including model deployment, monitoring, automated retraining, CI/CD, governance, and operational support.

Collaborate with business stakeholders, product teams, and technical leadership to identify AI/ML opportunities and translate business requirements into actionable solutions.

Mentor and lead teams of Data Scientists, ML Engineers, and Analytics professionals while establishing technical standards, best practices, and delivery excellence.

Champion advanced analytics, Generative AI, and data modernization initiatives while ensuring compliance, model performance, scalability, and long-term business value.

Required Qualifications:

Master’s or Ph.D. in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative field; bachelor’s degree with equivalent industry experience will also be considered.

12+ years of experience in Data Science, Machine Learning Engineering, or related fields, including 3–4+ years in a leadership or management role.

Deep expertise in AWS Cloud, AWS Data Lake architectures, Databricks, Apache Spark, MLOps, Python, and building production-grade AI/ML solutions at enterprise scale.

Proven experience leading global data science teams, driving AI/ML strategy, deploying Generative AI solutions, and managing large-scale data and analytics programs across multinational organizations

Key Skills

Education

Any Graduate