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Data Scientist II - Decision Science

Job in new westminster, Burnaby, BC, K3L, Canada
Listing for: Socket.dev
Full Time position
Listed on 2026-09-03
Job specializations:
  • IT/Tech
    Machine Learning/ ML Engineer, Data Scientist, AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 217000 - 326000 CAD Yearly CAD 217000.00 326000.00 YEAR
Job Description & How to Apply Below
Location: new westminster

Why Sony Interactive Entertainment?

Sony Interactive Entertainment isn’t just the Best Place to Play — it’s also the Best Place to Work. Sony Interactive Entertainment (SIE) is the company behind the Play Station brand. As a subsidiary of Sony Group Corporation, we’re part of a proud legacy of innovation and excellence. SIE is a dynamic technology company, delivering cutting‑edge hardware and network services to more than 100 million people and an entertainment leader, home to some of the most beloved and recognizable intellectual properties (IP) in the world.

Our role at SIE is to create and nurture the experiences under the Play Station brand, a name synonymous with entertainment excellence and creativity.

Data Scientist II - Decision Science Why Play Station?

Play Station isn’t just the Best Place to Play — it’s also the Best Place to Work. Today, we’re recognised as a global leader in entertainment, producing the Play Station family of products and services, including Play Station®5, Play Station®4, Play Station®VR, Play Station®Plus, acclaimed Play Station software titles from Play Station Studios, and more.

Play Station also strives to create an inclusive environment that empowers employees and embraces diversity. We welcome and encourage everyone who has a passion and curiosity for innovation, technology, and play to explore our open positions and join our growing global team.

The Play Station brand falls under Sony Interactive Entertainment, a wholly‑owned subsidiary of Sony Corporation.

Overview

Using data, you will play a crucial role in driving decision‑making and delivering impactful insights to our stakeholders. You will apply advanced analytical techniques, build Machine Learning (ML) models, and use experimentation and causal inference methods to solve sophisticated business problems related to platform engagement, product features, and games.

What you’ll be doing :
  • Apply advanced statistical and ML techniques to analyse large and complex datasets, extracting actionable insights in a commercial setting.
  • Apply your knowledge of Experimentation, Causal Inference, ML, and statistical modelling to develop robust predictive models and identify causal relationships.
  • Collaborate with cross‑functional teams to define business problems, formulate hypotheses, and design experiments to test them.
  • Independently extract and integrate data from multiple data systems, including writing complex SQL queries, to support analytical efforts.
  • Support the delivery of results and presentations to stakeholders, translating complex analyses into clear and actionable recommendations.
  • Stay up to date on the latest advancements in Data Science, including Causal Inference, Gen AI, and ML, and share knowledge and new ideas with the team.
What we’re looking for:
  • Master's Degree or Ph.D. in Applied Math, Economics, Statistics, Engineering, or a related quantitative field, plus at least 2 years of relevant industry experience, ideally in entertainment, gaming, technology, or a related consumer‑facing industry. A BA/BS Degree may also be considered based on additional relevant industry experience.
  • Advanced knowledge and experience applying ML methods using Python and SQL.
  • Familiarity with common development tools and practices, including version control systems (e.g., Git) and workflow management tools (e.g., Airflow).
  • Excellent communication and data storytelling skills, with the ability to effectively communicate technical concepts to non‑technical partners.
  • In‑depth understanding and experience using supervised and unsupervised ML techniques.
  • Understanding of Online Experimentation (large‑scale A/B tests) and Causal Inference methods, such as propensity score matching, synthetic control methods, and difference‑in‑differences, for accurately estimating causal relationships.
  • Knowledge of the gaming industry and relevant gaming titles is a plus.
  • Familiarity with Gen AI tools and pipelines is a plus.

At SIE, we consider several factors when setting each role’s base pay range, including the competitive benchmarking data for the market and geographic location.
Please note that the base pay range may vary in line with our hybrid…

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