Data Scientist, Product Analytics
@ Meta

Tel Aviv-Yafo, Tel Aviv District, Israel
$150,000
On Site
Full Time
Posted 21 days ago

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XXXXXXXXXX XXXXXXXXXXXXX XXXXXXXXXX******* @meta.com
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Job Details

About the Role

As a Data Scientist, Product Analytics at Meta, you will shape the future of people-facing and business-facing products across our family of applications including Facebook, Instagram, Messenger, WhatsApp, and Oculus. You will apply technical skills, analytical mindset, and product intuition using one of the richest data sets in the world and collaborate with diverse cross-functional teams.

Key Responsibilities

  • Work with large, complex data sets using various analytical and statistical approaches
  • Apply expertise in quantitative analysis, experimentation, and data mining
  • Define and measure success of product efforts through forecasting and goal setting
  • Identify opportunities to improve products and drive strategic roadmaps
  • Collaborate with Product, Engineering, and other teams to inform and execute strategies

Minimum Qualifications

Bachelor's degree in Mathematics, Statistics or a related field and 6+ years of experience with data querying languages (SQL), scripting languages (Python) and/or statistical software (R). Proven experience in solving analytical problems and leading data-driven projects.

Preferred Qualifications

Master's or Ph.D. Degree in a quantitative field.

About Meta

Meta builds technologies to connect people, foster communities and drive business growth. With a legacy of products that span digital connections and immersive experiences, Meta is at the forefront of innovation in social technology.

Key skills/competency

  • Data Analysis
  • Quantitative
  • SQL
  • Python
  • Statistical Modeling
  • Experimentation
  • Product Analytics
  • Data Mining
  • Cross-functional
  • Insights
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How to Get Hired at Meta

🎯 Tips for Getting Hired

  • Research Meta's culture: Understand their mission and values.
  • Customize your resume: Highlight advanced data analytics skills.
  • Showcase projects: Emphasize quantitative and product impact.
  • Prepare for interviews: Practice data-driven storytelling and technical tests.

📝 Interview Preparation Advice

Technical Preparation

Review SQL query optimization techniques.
Practice Python data analysis libraries.
Study statistical modeling methods.
Refresh machine learning experiment design.

Behavioral Questions

Describe teamwork in data project settings.
Explain handling conflicting project priorities.
Discuss challenging data analysis scenarios.
Share a time you influenced product decisions.

Frequently Asked Questions