Data Scientist

This is a hybrid role in Redmond, WA that will start from March to June with a likely extension up to 18 months.

In this role, you will be responsible for driving insights that inform our Player Lifecycle Marketing efforts. You’ll partner with marketing and engineering teams to ensure a robust pipeline from database to reporting for Player Lifecycle marketing campaigns. You will analyze and make recommendations on the results of marketing A/B tests and evaluate the impact of evergreen campaigns on key metrics.

You will develop and lead analysis that identify key drivers of monetization, engagement, and retention.

What You’ll Do
As a key contributor, you will delve into vast datasets to uncover critical insights, playing a crucial role in optimizing player lifecycle initiatives. Your work will involve analyzing marketing campaign performance, identifying key drivers of player behavior, and making strategic recommendations that directly influence business outcomes.

• Perform data exploration, profiling and proof-of-concept table creation to assist engineering partners in building and improving the production data environment.
• Maintain and improve dashboards in Power BI that enable stakeholders to understand the impact of specific campaigns as well as the broader Player Lifecycle Messaging (PLM) impact.
• Build and maintain causal inference frameworks
• Provide analysis and recommendations on how to best optimize campaigns for player engagement, retention, and post-sale monetization, with clear prioritization of “what to do next” with expected impact.
  • Synthesize insight narratives:
    Turn analyses into clear, decision-ready narratives that connect activity to gaming business outcomes (e.g., engagement, retention, Marketplace/Realms monetization), answering What happened? Why? So what? Now what?
  • Executive-ready communication:
    Produce clear readouts (deck-ready visuals, annotated dashboards, short written summaries) that communicate the “through line” from campaign setup → player behavior change → business implication—tailored to technical and non-technical audiences.
  • Create shared understanding of the funnel:
    Help stakeholders understand how performance fits into the broader game ecosystem by building and socializing lifecycle frameworks, and by clarifying tradeoffs (e.g., engagement vs. monetization impacts).
  • Communicate clearly across disciplines:
    Provide clear, consistent, and concise communication with varied stakeholders
• Conduct analysis to identify statistically significant impact from campaigns and provide recommendations tests to add to the roadmap
• Synthesize campaign results into recommendations for stakeholders, clearly communicating assumptions, limitations, and confidence in results
• Collaborate with marketing, PM, and engineering stakeholders to define success metrics, measurement plans, and instrumentation needs for campaigns and lifecycle initiatives.
• Provide clear, consistent and concise communication and presentation with varied stakeholders including data engineer, PM and marketing partners.

Must-Have Qualifications

• 7+ years of overall experience in data science or analytics.
• 5 years of experience in data analytics, including data profiling, table creation and marketing analytics.
• 5 years of experience with SQL, bonus if familiar with Spark
  
  SQL, Databricks, or Azure Data Explorer.
• 3 years of experience with dashboarding tools, Power BI preferred.
• Experience with marketing tools such as Braze, Salesforce, Clever Tap
• Proficient in Python, bonus if familiar with PySpark.
• Able to work in a collaborative, diverse and fast-paced team.
• Excellent analytical, and problem-solving skills and autonomy when faced with solving data problems.
• Excellent verbal, visual and written communication skills.
• Insight synthesis & business framing:
  Demonstrated ability to translate complex analyses into clear insights, implications, and recommendations—not just charts—tailored to the audience.
• Data visualization & narrative clarity:
  Strong visual communication skills: chooses the right chart/story structure, highlights drivers, quantifies impact, and makes results easy to interpret (including clear caveats).
• Stakeholder-ready outputs:
  Comf…