Electronic Arts

Description/Background

What does the EA IT Data & Insights Engineering Team do?

Electronic Arts is a global leader in digital interactive entertainment. The Company's game franchises are offered as both packaged goods products and online services delivered through Internet-connected consoles, personal computers, mobile phones, and tablets. EA has more than 275 million registered players and operates in 75 countries. 

Our team, EA IT Data and Insights is responsible for the planning, building and deployment of Enterprise Data Insights, Enterprise Integration and Business Intelligence solutions for EA. The team is currently focused on a multi-year effort to build the next generation data Insights to empower EA with trusted and actionable insights to make faster decisions, uncover new revenue opportunities and optimize business performance. Enterprise Integration, a shared service, is a key enabler for ensuring timely availability of accurate and quality data in business applications and the enterprise data warehouse. 

What will you be doing?

You will work with other Senior data engineers and architects to implement strategies directed at acquiring data and promoting the development of new insights across the business. The Data Engineer owns and extends the business’s data pipeline through the collection, storage, processing, and transformation of large datasets. It is his duty to monitor the existing metrics, analyze data, and lead partnership with other Data and Analytics teams in an effort to identify and implement system and process improvements.

As a part of data engineering team, you’ll be responsible for improving the quality of our decisions using data and the scientific method. Your work will generate tools and insights that inform product and business decisions throughout the company and across the product lifecycle, from ideation and research to launch and iteration.

As part of this role, the data science engineer will work on multiple databases including Snowflake cloud data warehouse, Oracle, SQL Server etc and also leverage AWS and/or azure cloud platform for designing and development of different solutions supporting business for data analysis and reporting. As a data science engineer, knowledge of statistical programming languages like R, Python, and database query languages like SQL, Hive, Pig is desirable. Familiarity with Scala, Java, or C++ is an added advantage.  Good applied statistical skills, including knowledge of statistical tests, distributions, regression, maximum likelihood estimators, etc. Proficiency in statistics is essential for this role. Good knowledge of machine learning methods like k-Nearest Neighbors, Naive Bayes, SVM, Decision Forests is required for this role.

Our Senior Engineers love to experiment with leading-edge technology, dive deep into code and work as part of a team of programming experts who define and solve big problems and build powerful automation tools. You must ensure stellar product quality, and work under the technical guidance of Product & Program Managers as they communicate user needs and product requirements. This role is for an entry-level engineer who loves the challenge of building distributed, high availability, and resilient systems. You will be interacting with product managers, project leads, architects, quality engineers, and infrastructure engineers across different locations.

Responsibilities

• Data mining or extracting usable data from valuable data sources. • Using machine learning tools to select features, create and optimize classifiers. • Carrying out pre-processing of structured and unstructured data. • Enhancing data collection procedures to include all relevant information for developing analytic systems. • Processing, cleansing, and validating the integrity of data to be used for analysis. • Analysing large amounts of information to find patterns and solutions. • Developing prediction systems and machine learning algorithms. • Analyse data for trends and patterns and interpret data with clear objectives in mind • Implement analytical models in production by collaborating with software developers and machine-learning engineers • Derive insights from data to influence product roadmaps and drive business results. • Apply advanced statistical methods to model user behavior. • Presenting results in a clear manner • Understand and comply with the established software development life cycle methodology. • Proactively identify opportunities for process improvements and implements the same. • Keep current with industry technologies and tools in the integration and analytics domain.

Skills Must Have

•  Programming Skills ● Understanding around Object Oriented Programming with basic coding experience for the same. ● Familiarity with data analysis techniques, statistical modeling, and machine learning concepts. ● Knowledge of programming languages such as Pythonor Rfor data manipulation and analysis. ● Understanding of basic mathematical concepts and statistical methods commonly used in data science. ● Knowledge of SQL or No-SQL databases like MySQL, DynamoDB, etc. ● Knowledge and working experience with SCSS (preferably Git) and best practices ● Openness to work with cross-functional teams such as Design and Product teams in an Agile work environment.

Extra Points

•  Knowledge of cloud platforms like AWS, Azure, etc and related serverless technologies. ● Knowledge of code build and deployment process using CI/CD pipeline and automation (e.g. GitLab, Jenkins, Cloudbees) ● Strong problem-solving skills and the ability to think analytically to approach complex business problems. ● Strong attention to detail to ensure accuracy in data analysis and modeling. ● A passion for learning and exploring new technologies, tools, and techniques in the field of data science.

Qualifications

•  Completed/Pursuing engineering in data science, computer science, statistics, mathematics, or equivalent experience • Exposure to distributed, network, and systems programming in Linux, Windows or macOS environment • Openness to take projects from initial spec/requirements through design and implementation, testing and debugging, documentation, and installation in an Agile environment • Strong written and oral communication skills are essential • Ability to stay on top of technology, participate in brainstorming sessions and contribute ideas to our products and tech stack • Self-starter with an eagerness to constantly learn and pass/share the knowledge along to the team. • Strong sense of ownership/‘can do’ attitude and high attention to detail • Ability to work in a distributed global team • Ability to dive into difficult problems and deliver results on time and on spec • Demonstrate a high level of creativity and problem solving