Electronic Arts Is Hiring for Data Science Intern

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Job Details

  1. Company Name: Electronic Arts (EA)
  2. Job Role: Data Science Intern
  3. Department: CT – Infrastructure & Platform
  4. Location: Hyderabad, Telangana, India
  5. Job ID: 215937
  6. Job Type: Internship – Temporary Employee
  7. Work Model: Hybrid
  8. Qualification: Bachelor’s or Master’s degree in Computer Science, Computer Engineering, Software Engineering, or a related field
  9. Experience Required: Not specified; candidates with relevant academic knowledge and practical machine learning skills may be suitable.
  10. Estimated Salary/Stipend: ₹30,000–₹70,000 per month
  11. Key Technologies: Python, R, TensorFlow, PyTorch, Scikit-learn, cloud platforms, Large Language Models (LLMs), and AI agents.

The stipend range is an estimate for this internship in Hyderabad, not an officially confirmed amount from EA. Actual compensation may vary based on the internship terms and candidate profile.

Job Overview

Electronic Arts is offering a Data Science Intern opportunity in Hyderabad, India, within its Digital Platform organisation. The intern will work on machine learning solutions that address real-world challenges in the gaming industry. Responsibilities include preparing large datasets, developing custom machine learning models, deploying models to production, and monitoring their performance. The role also involves learning about LLMs, AI agents, cloud platforms, and scalable applications. This opportunity is suitable for students or candidates with a relevant technical background who have strong programming, analytical, and problem-solving skills.

Key Responsibilities

  1. Work with product managers, senior engineers, and team members to understand project requirements.
  2. Develop prototypes and build large-scale distributed applications.
  3. Design and implement custom machine learning models for gaming-related challenges.
  4. Clean, preprocess, and analyse large datasets.
  5. Maintain data quality, consistency, and accuracy.
  6. Handle imbalanced datasets to improve machine learning model performance.
  7. Deploy and host machine learning models using suitable technologies.
  8. Ensure deployed models are scalable, reliable, and suitable for production environments.
  9. Monitor model performance and maintain models after deployment.
  10. Develop feedback loops to improve models continuously.
  11. Identify and reduce bias in machine learning models.
  12. Collaborate with cross-functional teams to understand business requirements.
  13. Convert business needs into technical solutions and system designs.
  14. Document development processes, model performance, and findings.
  15. Provide recommendations and insights based on data analysis and model evaluation.
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Eligibility Criteria

  1. Candidates should have a bachelor’s or master’s degree in Computer Science, Software Engineering, Computer Engineering, or a related field.
  2. Applicants should have a strong foundation in computer science fundamentals.
  3. Candidates should understand algorithms, data structures, and design patterns.
  4. Applicants should have knowledge of Python or R programming.
  5. Candidates should understand data preprocessing and machine learning concepts.
  6. Applicants should be familiar with machine learning libraries such as TensorFlow, PyTorch, or Scikit-learn.
  7. Candidates should understand model evaluation techniques and performance metrics.
  8. Knowledge of cloud platforms such as AWS, Google Cloud Platform, or Microsoft Azure is beneficial.
  9. Applicants should understand LLM architecture, fine-tuning, and training.
  10. Candidates should have a good understanding of AI agents.
  11. Applicants should demonstrate strong problem-solving and analytical skills.
  12. Candidates should be comfortable working in a collaborative, fast-paced environment.
  13. Applicants should be able to communicate technical concepts clearly.
  14. Candidates should be able to translate business requirements into technical designs.
  15. Applicants should be willing to learn, work through unclear requirements, and deliver solutions iteratively.

Required Skills

  1. Python or R programming.
  2. Machine learning model development.
  3. TensorFlow, PyTorch, or Scikit-learn.
  4. Data cleaning and preprocessing.
  5. Handling imbalanced datasets.
  6. Model evaluation and performance measurement.
  7. Machine learning model deployment and monitoring.
  8. Knowledge of cloud computing platforms.
  9. Understanding of algorithms and data structures.
  10. Familiarity with CI/CD processes.
  11. Knowledge of Large Language Models (LLMs).
  12. Understanding of LLM fine-tuning and training.
  13. Knowledge of AI agents and their applications.
  14. Ability to identify and reduce model bias.
  15. Strong communication, teamwork, and problem-solving skills.

Why Join Electronic Arts?

  1. Practical industry experience: Work on real-world machine learning problems in the gaming industry.
  2. Advanced technology exposure: Learn about AI, machine learning, LLMs, and AI agents.
  3. Large-scale projects: Explore solutions designed to support games with millions of active users.
  4. Professional mentorship: Collaborate with experienced engineers and product managers.
  5. Cloud technology experience: Gain exposure to cloud-based machine learning deployment.
  6. Collaborative work culture: Work with cross-functional teams in a global organisation.
  7. Learning opportunities: Strengthen technical, analytical, and problem-solving abilities.
  8. Creative environment: Work at a company known for interactive entertainment and gaming experiences.
  9. Employee well-being: EA offers benefit programmes that may include healthcare, mental well-being support, paid time off, and other benefits, depending on local eligibility.
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