Staff Data Scientist – Experiments & Causal Inference

playstation

United States

Remote

USD 212,200 - 318,200

Full time

14 days+

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Benefits offered by this job

Medical benefits
Dental benefits
Employee discounts

Job summary

Sony Interactive Entertainment is seeking a Staff Data Scientist in Experimentation & Measurement to lead design and interpretation of experiments shaping PlayStation experiences worldwide.

You will apply causal inference, design A/B tests, and collaborate with product, engineering, and marketing to embed experimentation into development cycles while mentoring other data scientists and influencing senior leadership.

Qualifications

  • Bachelor’s degree or equivalent.
  • 6+ years in data science experimentation/causal inference.
  • Proficiency in SQL and Python.
  • Experience with machine learning is a plus.
  • Influence product decisions with insights.
  • Experience contributing to experimental frameworks.

Responsibilities

  • Design, execute, and interpret A/B tests and quasi-experiments.
  • Partner with product, engineering, and marketing to embed experimentation.
  • Mentor data scientists and provide technical direction.
  • Lead frameworks, tools, and documentation for experimentation scalability.
  • Extract and analyze data using SQL, Python, and other tools.
  • Communicate findings clearly to stakeholders.
  • Stay current on causal analysis methodologies.
  • Influence PlayStation product evolution through insights.

Skills

Statistical analysis
A/B testing
Causal inference
SQL
Python
Product impact

Education

Bachelor’s degree or equivalent
Master’s or PhD in Statistics/Econometrics

Tools

Statistical software

Job description

Sony Interactive Entertainment is seeking a Staff Data Scientist in Experimentation & Measurement to lead design and interpretation of experiments shaping PlayStation experiences worldwide.

You will apply causal inference, design A/B tests, and collaborate with product, engineering, and marketing to embed experimentation into development cycles while mentoring other data scientists and influencing senior leadership.

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