Twitter is what’s happening and what people are talking about right now. For us, life's not about a job, it's about purpose. We believe real change starts with conversation. Here, your voice matters. Come as you are and together we'll do what's right (not what's easy) to serve the public conversation.

Are you interested in building a better personalization experience for hundreds of millions of users on Twitter?

The Personalization Data Science team is working closely with Product, Engineering, Design, and Research teams to drive personalized experience across the Twitter app. The team is responsible for developing data science and machine learning solutions for understanding user behavior (acquisition, retention, churn, etc.) and defining product personalization strategy through measurement design, experimentation, causal analysis, and post-launch learning.

If you are looking for a high visibility role where you have the opportunity to dive deep into personalized ranking, technically lead the team toward building relevant DS solutions, and present findings to cross-functional teams and leadership, this is the role for you!

What you’ll be doing 

As a data scientist on the team you will:

• Build long term product vision and strategy and scope out the area for the team.

• Generate product ideas that drive Twitter’s global participation and monetization objectives.

• Understand the complex E2E recommendation system and identify the bottlenecks and opportunities.

• Design, implement, and analyze experiments to determine how changes to the platform affect user behavior and refine our understanding of users’ interests and the communities they form.

• Conduct analyses to derive strategic insights from vast datasets across different product areas.

• Apply ML and statistics techniques to model user behavior, identify causal impact and attribution, build and benchmark metrics, and forecast future performance.

• Communicate findings to executives and cross-functional product teams by translating statistically rigorous analyses towards business impact.

• Improve the reproductivity and efficiency of analysis work through code review and other established processes.

Help drive the team roadmap, encourage technical excellence, keep on track of research trends in the fields of personalized recommendation, and train and mentor junior team members.

• Master/PhD in a quantitative field and 5+ years of experience 

• Experience with ML and statistical knowledge (e.g advanced statistical techniques for A/B testing, methods for experimental design, or observational causal inference)

• Track record of executing independent projects and leading complex, cross-functional projects with several dependencies.

• Strong proficiency with Python / R and SQL.

• Solid written and verbal communication skills, especially for executive audiences. 

• Experience mentoring junior data scientists and enthusiasm for building out a new data science community.

All your information will be kept confidential according to EEO guidelines.