Associate Data Scientist

Electronic Arts (EA), one of the world's leading interactive entertainment companies, is hiring an Associate Data Scientist for its Data & Insights team in Hyderabad. This role presents an outstanding opportunity for fresh graduates and early-career professionals who are passionate about data science, analytics, machine learning, and business intelligence. As an Associate Data Scientist, you will work with large-scale datasets generated from millions of players worldwide to uncover meaningful insights that influence product development, game performance, player engagement, and business strategy. By leveraging statistical analysis, programming, and machine learning techniques, you will help transform raw data into actionable intelligence that drives innovation across EA's globally recognized gaming portfolio. In this role, you will collaborate closely with data scientists, engineers, product managers, marketers, and business stakeholders to solve complex analytical problems. Your daily responsibilities will include performing exploratory data analysis (EDA), querying and transforming data using SQL, building analytical datasets, developing dashboards, creating predictive models, and supporting experimentation initiatives such as A/B testing. You will utilize programming languages including Python and R, along with modern visualization platforms like Tableau and Power BI, to communicate findings effectively. The position also offers exposure to cloud-based data platforms, large-scale analytics, and machine learning workflows, providing an excellent foundation for long-term growth in data science and artificial intelligence.

Perform exploratory data analysis (EDA) to identify patterns, trends, correlations, and business opportunities from large player, product, and operational datasets. Collect, clean, validate, transform, and organize structured and unstructured data from multiple sources to create reliable datasets for analysis. Apply statistical methods, hypothesis testing, probability concepts, and foundational machine learning techniques to solve business and product challenges. Build predictive models, forecasting solutions, and analytical frameworks that support product performance evaluation and strategic decision-making. Design and develop interactive dashboards, reports, and data visualizations using business intelligence tools to present actionable insights. Collaborate with product managers, software engineers, marketing teams, analysts, and business stakeholders to translate business questions into analytical solutions. Write optimized SQL queries and develop Python or R scripts to automate data processing, reporting, and analytical workflows. Support experimentation initiatives including A/B testing, feature evaluation, and performance measurement to improve player engagement and business outcomes. Maintain analytical models, validate data quality, document methodologies, and follow software development best practices for reproducible analytics. Communicate technical findings and business recommendations clearly to both technical and non-technical audiences through reports and presentations. Continuously research emerging trends in data science, artificial intelligence, machine learning, and advanced analytics to improve organizational capabilities. Contribute to cross-functional projects by providing data-driven insights that enhance product innovation, customer experience, and operational efficiency.

Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Economics, Engineering, Information Technology, or another quantitative discipline from a recognized university. Zero to three years of experience in Data Science, Business Analytics, Machine Learning, Business Intelligence, Data Analytics, or related quantitative fields. Strong understanding of statistics, probability, hypothesis testing, exploratory data analysis, and data interpretation techniques. Proficiency in SQL for querying relational databases, data extraction, data transformation, and analytical reporting. Working knowledge of Python, R, or similar programming languages used for statistical analysis, machine learning, and automation. Basic understanding of machine learning algorithms, predictive modeling, model evaluation, feature engineering, and data preprocessing techniques. Familiarity with structured and unstructured datasets along with data visualization tools such as Tableau, Power BI, Looker, or similar platforms. Knowledge of cloud technologies including AWS, Microsoft Azure, Google Cloud Platform (GCP), Snowflake, or Databricks will be considered an added advantage. Excellent analytical thinking, logical reasoning, communication, presentation, and problem-solving skills with strong attention to detail. Passion for gaming, digital products, artificial intelligence, player analytics, experimentation, and continuous learning in modern data science technologies.