Lead Data Scientist - Store Recommendations

Job Description

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Data-driven decision-making is essential to game development at EA. We're looking for a thoughtful and disciplined Lead Data Scientist with deep statistical modeling experience, strong data engineering experience and a passion for games and digital technologies. The biggest and single most important aspect that we look for in aspiring colleagues is people who enjoy the joy of discovery.

You will report to a Director of Data Science within EA's central Data and Analytics (DnA) organization. You will work with top data science talent to build live services features like store recommendations across all EA titles that will lead to a unique opportunity to affect the games played by millions of players. You're passionate about elevating insights to be actionable across projects, and accelerating learning through data-driven testing.

You will bring expertise in the area of AI, ML, and engineering, to create best practices for EA's store recommendations and personalization, helping to surface interesting items to each player.

What you'll do:
• Work directly with game teams/partners (internal clients) to understand their offerings/domain and create data science products and solutions to solve for their use cases.
• Partner with our team lead for Recommendations and Personalization to help generalize Store Recommendations algorithms across titles.
• Coach and mentor Data Scientists and Senior Data Scientists for Recommendations and Personalization, ensuring technical best practices and guiding stakeholder communication.
• Ensure sound methodology and experimental design, and guide the direction of each project from start to finish.
• Effectively communicate data science projects and products to stakeholders, including those with non-data science backgrounds.
• Design, improve and work with our data pipeline that transfers and processes petabytes of data using S3, Kubernetes, Sagemaker, GCP, Python, Apache Kafka, & Hive.
• Use data manipulation, processing, and data visualizations to aid in your modeling efforts.
• Assist game teams and data teams in making important decisions.

You have:
• 6+ years of professional experience manipulating data sets, building statistical models and productizing models along with experience applying Data Science methodologies to real-world problems.
• Ph.D./Master's in Statistics, Mathematics, Computer Science, or another quantitative field encouraged.
• Strong expertise in building, deploying, and testing recommendations algorithms.
• Experienced in analyzing extremely complex, multi-dimensional data sets with a variety of tools.
• Superior verbal, visual, and written communication skills to educate and work with cross-functional teams.
• Experience using Python, SQL, PyTorch/TensorFlow, Hive/Hadoop, and AWS/GCP.
• Experience guiding and mentoring more junior Data Scientists.
• Expertise and interest in video games, understanding typical business models, game development practices and technology is a big plus.

Ceci ne s'applique pas au Québec. COMPENSATION AND BENEFITS The ranges listed below are what EA in good faith expects to pay applicants for this role in these locations at the time of this posting. If you reside in a different location, a recruiter will advise on the applicable range and benefits. Pay offered will be determined based on a number of relevant business and candidate factors (e.g. education, qualifications, certifications, experience, skills, geographic location, or business needs). BASE SALARY RANGES
• British Columbia (depending on location e.g. Vancouver vs. Victoria)
• $133,400 - $193,200 CAD

Base salary is just one part of the overall compensation at EA. We also offer a package of benefits including vacation (3 weeks per year to start), 10 days per year of sick time, paid top-up to EI/QPIP benefits up to 100% of base salary when you welcome a new child (12 weeks for maternity, and 4 weeks for parental/adoption leave), extended health/dental/vision coverage, life insurance, disability insurance, retirement plan to regular full-time employees. Certain roles may also be eligible for bonus and equity.

Jobcode: Reference SBJ-d8wppk-18-117-172-52-42 in your application.