8+ years of hands-on experience in Data Science and Data Engineering.
Expert-level proficiency in Python and architectural patterns for distributed computing.
4+ years of experience in MLOps and productionalization of machine learning models.
Strong understanding of data architecture and real-time streaming architectures like Kafka or Spark Streaming.
Experience with cloud infrastructure (AWS/Azure/GCP) and containerization (Docker/Kubernetes).
Excellent system design and analytical skills focused on model governance and scalability.
Superior communication and leadership skills for aligning technical and business strategies.
Responsibilities
Design and deploy enterprise-scale analytical solutions.
Lead the end-to-end lifecycle of machine learning models, focusing on CI/CD.
Develop and implement data architecture and real-time streaming solutions.
Build scalable environments for model training and inference using cloud infrastructure.
Drive the adoption of innovative data technologies across cross-functional teams.
Define technical standards and ensure model governance and security.
Communicate architectural trade-offs to executive stakeholders.
Benefits
Opportunity to work with cutting-edge data technologies.
Collaborative environment with cross-functional teams.
Leadership role with influence over technical roadmaps.
Focus on innovation and continuous improvement in data solutions.
Full Job Description
Job Description :
8+ years of hands-on experience in Data Science and Data Engineering, with a proven track record of designing and deploying enterprise-scale analytical solutions.
Expert-level proficiency in Python, alongside deep knowledge of Architectural Patterns for distributed computing and large-scale data processing (a must-have requirement).
4+ years of dedicated experience in MLOps and Productionalization, focusing on the end-to-end lifecycle of machine learning models (CI/CD for ML).
Strong understanding of Data Architecture, and real-time streaming architectures (e.g., Kafka or Spark Streaming).
Experience with Cloud Infrastructure (AWS/Azure/GCP) and containerization (Docker/Kubernetes) to build scalable, resilient environment for model training and inference.
Excellent system design and analytical skills, with a focus on model governance, security, and scalability of AI solutions.
Superior communication and leadership skills, with the ability to align technical roadmaps with business strategy and explain architectural trade-offs to executive stakeholders.
Proven ability to lead cross-functional teams, define technical standards, and drive the adoption of innovative data technologies in a fast-paced environment.
About Virtusa Corporation
Virtusa Corporation is a global provider of digital business strategy, digital engineering, and information technology (IT) services and solutions. The company helps its clients transform their businesses through innovative technology solutions that enable them to improve customer engagement, increase operational efficiency, and drive revenue growth. Virtusa Corporation was founded in 1996 and is headquartered in Southborough, Massachusetts. The company has over 20,000 employees and operates in over 30 countries around the world. Virtusa Corporation is committed to sustainability and has received numerous awards for its environmental and social responsibility initiatives.
