About Careertakes

👉 Important disclosure: Careertakes is a third-party recruiting platform supporting this hiring process. If selected, you will be employed directly by our client, Social Networking Platforms.

Applicants for this role may also receive access to additional matched opportunities through the Careertakes platform.

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What You’ll Do

As a Data Scientist (PGC) for a confidential client in the Social Networking Platforms industry, you will support analytics and experimentation that shape professionally generated content (PGC) strategy and product decisions.

• Participate in data analysis across PGC content and product areas to explore supply/demand dynamics, user behavior, and creator ecosystems.
• Identify testable business questions and growth opportunities; translate them into measurable hypotheses.
• Design and analyze A/B tests and experiments; evaluate feature and strategy changes and produce clear, actionable findings.
• Build and maintain core metrics, dashboards, and analytical definitions for continuous business tracking and decision-making.
• Partner with Product, Operations, Engineering, and Machine Learning teams to support strategy evaluation across recommendation, distribution, and creator growth.
• Investigate metric anomalies and lead root-cause analyses.
• Communicate results and recommendations to cross-functional stakeholders and drive analytical workstreams toward independent ownership.

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What We’re Looking For

Minimum qualifications:

• Bachelor’s degree or higher in Data Science, Statistics, Econometrics, Mathematics, Computer Science, or a related field.
• 1+ years of experience in data analysis, data science, or relevant internship/full-time roles.
• Solid foundation in statistics: A/B testing, hypothesis testing, regression analysis, and common analytical methods.
• Strong SQL proficiency and experience using Python or R for data processing, basic modeling, and visualization.
• Structured problem-solving and the ability to break business problems into analyzable and testable data questions.
• Clear written and verbal communication; ability to present analytical process and results to stakeholders.

Preferred qualifications:

• Experience or coursework in causal inference.
• Interest or experience in content products, recommendation systems, creator ecosystems, or user-growth analytics.
• Experience working on cross-region or international projects is a plus.
• Strong curiosity, self-drive, and learning agility.

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Compensation & Benefits

• Base salary range for this role in San Jose, CA: $136,800 - $216,000 annually.
• Compensation may vary based on qualifications, skills, competencies, experience, and work location. Total compensation may include discretionary bonuses/incentives and equity (e.g., restricted stock units).
• Benefits typically include day-one access to medical, dental, and vision insurance, a 401(k) with company match (or local equivalent), paid parental leave, disability coverage, life insurance, and paid time off (holidays, sick days, and personal time). Specific benefits may vary by employment type and work location.

If you require a reasonable accommodation during the hiring process (for a disability, pregnancy, sincerely held religious belief, or other reasons protected by law), please request assistance through the Careertakes platform so we can coordinate with our client.

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About Working with Our Client

You will join a confidential client operating in Social Networking Platforms, working on content and recommendation products that reach large, diverse user bases. The role offers hands-on exposure to product analytics, experimentation, creator-growth strategies, and cross-functional collaboration with product and engineering teams.

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Equal Opportunity & Hiring Transparency

Careertakes and our client are Equal Opportunity Employers committed to building a diverse and inclusive workforce. We prohibit discrimination or harassment of any kind. To support a fair and efficient hiring process, AI tools may be used to assist with application review or resume screening. These tools do not replace human decision-making. Final hiring decisions are made by people.

If you have questions about how your data is used, please contact us directly.