EY GDS AI and Data recruitment Drive Direct interview chance apply now Full Time

What’s in it for you?

• Rewards and recognitions that focus on your physical, emotional, financial and social well-being
• Work flexibly and meet your obligations to stakeholders, family, yourself and the community
• Learning and development programs that help you succeed anywhere in the working world
• Take up opportunities at various EY GDS teams and locations based on business need, qualifications and experience
• Be a force for social good. Join over 4,00,000 like-minded EY people making a tremendous impact on the working world

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About Program

EY GDS is hiring across AI_Data roles in Technology Consulting—and this is your chance to work on real-world problems, leading-edge platforms, and future-shaping solutions. Join a team where data meets purpose, innovation scales globally, and your skills help shape what’s next for businesses worldwide.
If you’re ready to build, innovate, and lead with confidence, we’re ready for you.

Key Responsibilities

• Data Pipeline & Engineering: Develop, optimize, and maintain robust ETL processes and data warehouses for efficient data ingestion and storage.
• AI Model Development: Build, train, and deploy machine learning algorithms, neural networks, and predictive models.
• Data Analysis & Insights: Analyze large datasets to identify patterns and provide actionable insights for business decisions.
• Integration & Generative AI: Integrate AI/GenAI models into existing systems to enhance functionality and create simulations.
• Data Governance & Quality: Ensure the accuracy, security, and consistency of data by establishing data modeling standards and documentation.
• Collaboration: Work with cross-functional teams to translate business requirements into technical specifications. 

Required Skills and Qualifications

• Technical Skills: Proficiency in Python, SQL, Java, or Scala; experience with frameworks like TensorFlow, PyTorch, or Scikit-learn.
• Data Tools: Experience with big data technologies (Apache Spark, Hadoop) and cloud platforms (AWS, GCP, Azure).
• Technical Knowledge: Deep understanding of data structures, algorithms, machine learning principles, and NLP techniques.
• Education: Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or a related field.
• Soft Skills: Strong analytical, problem-solving, and communication skills to convey complex technical concepts to stakeholders.   

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