Electronic Arts Career Drive 2025 Hiring Data Science Intern

By
Cyber Tecz
-
21
Electronic Arts Career Drive 2025
Electronic Arts Career Drive 2025

Electronic Arts Career Drive 2025 | Data Science Intern | Hyderabad India

Electronic Arts (EA), a global leader in interactive entertainment, has opened applications for its Career Drive 2025 to hire Data Science Interns. This internship offers freshers and students the opportunity to work on real-world gaming data, analytics, and machine learning models that enhance player experiences worldwide. If you’re passionate about gaming, data, and innovation, this is your chance to learn from the best in the industry. Apply now to EA’s Data Science Internship 2025 and take your first step into the world of data-driven gaming!

Job Details

  • Designation: Data Science Intern
  • Company: Electronic Arts
  • Educational Qualification: BE, BTech, BCA, BSc,
  • Experience Required: 0–1 year (Freshers eligible)
  • Location: Hyderabad India
  • Compensation: Best in Industry

Role Overview:

You’ll join a hands-on, fast-moving team to build data and ML solutions with an emphasis on Python and software craftsmanship. You’ll write clean, well-tested code; wrangle large datasets; engineer features; train/evaluate models; and help move prototypes toward production in collaboration with senior engineers and architects.

Must‑Have Skills (Core Hiring Bar)

  • Python mastery for data work: pandas, NumPy, scikit‑learn; writing reusable functions/classes; debugging and profiling; packaging basics.
  • Strong coding fundamentals: data structures & algorithms, OOP, modular design, unit testing (pytest or similar), version control (Git), and code reviews.
  • ML & DS foundations: supervised learning (linear/logistic regression, trees/ensembles), regularization, bias/variance, cross‑validation, feature scaling/encoding, and model evaluation (AUC/ROC, F1, RMSE/MAE, calibration).
  • Statistics for data analysis: sampling, hypothesis testing, confidence intervals, distributions; ability to choose appropriate tests and interpret results.
  • Solid SQL for data extraction/joins/aggregations and working knowledge of query optimization basics, along with proficiency in Git (GitHub/GitLab workflows, branching, pushing, merging).
  • Data wrangling & EDA: handling missing/outliers, joins/pivots, time‑series/tabular transforms, clear visualizations (matplotlib/plotly) and narrative summaries.
  • Problem solving & ownership: ability to define the problem, design experiments, deliver incremental value, and document decisions.
  • Communication: concise written docs/notebooks and clear verbal explanations tailored to technical/non‑technical partners.

Good‑to‑Have Skills (Differentiators)

  • Cloud & data platforms: exposure to Snowflake/BigQuery/Redshift; familiarity with AWS or Azure basics (e.g., S3/Blob, compute, IAM concepts).
  • Pipelines & orchestration: experience with Airflow/Prefect or similar; understanding of batch vs. streaming concepts.
  • Software craftsmanship extras: Makefiles/poetry/pip-tools, pre‑commit, linters/formatters, logging & observability, simple CLI tools.
  • MLOps/productionization: model persistence (joblib/ONNX), reproducibility (seeds/environments), lightweight API serving (FastAPI/Flask), and tracking (MLflow/Weights & Biases).
  • Advanced ML: gradient boosting (XGBoost/LightGBM/CatBoost), time‑series forecasting basics, recommendation, Neural Networks and NLP fundamentals.
  • Big data: PySpark or Spark SQL for distributed transforms; understanding of partitioning and performance trade‑offs.
  • Visualization & storytelling: dashboards in Plotly Dash/Streamlit; crafting stakeholder‑ready summaries.
  • Competitive programming/problem-solving practice: experience with LeetCode, CodeChef, or similar platforms to strengthen algorithmic and coding proficiency.
  • Other languages: basic R or SQL dialects; familiarity with JVM/C++/Scala is a plus.

What You’ll Do

  • Build robust Python modules and notebooks for data ingestion, feature engineering, and model training (primarily with pandas, NumPy, and scikit-learn).
  • Author clear, maintainable code using OOP, type hints, docstrings, and unit/integration tests; participate in code reviews and follow Git-based workflows.
  • Explore datasets to define problem statements, create hypotheses, and conduct EDA with appropriate visualization and summary statistics.
  • Implement and evaluate baseline and advanced ML models; select metrics, design experiments, and apply cross-validation.
  • Apply solid SQL to extract/transform data; collaborate on building reliable data pipelines to support analytics and reporting use cases.
  • Communicate results with crisp narratives, dashboards/plots, and reproducible notebooks; translate findings into product and business recommendations.
  • Contribute to best practices in the team’s development lifecycle (automation, CI, documentation) and proactively suggest improvements.

Interested students can apply directly at 👉 Electronic Arts Career Drive 2025

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