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Meta Data Scientist, Messenger in San Francisco, California

Summary:

We are seeking an experienced Data Scientist to join the Messenger Data Science team.A successful candidate will be responsible for tackling high priority product challenges for Messenger and IG Direct messaging experiences. This individual will be an expereinced leader on the team working across many Messenger product areas and with data scientists both within Messenger and across Meta. Specifically, in this role this person can expect to lead:1. Our Return on Investment (ROI) effortsquantifying ROI of messaging products and features. This involves analyzing the costs and benefits associated with new and existing features, and using this information to make data-driven decisions about how to allocate resources and prioritize efforts.2. The largest messaging priorities.Given this is a central role reporting to the head of Messenger product data science, this individual will tackle the largest opportunities and challenges in the messaging space. This can range from new 0-1 bets, improvement of high impact features or new efforts around monetization or costs. This individual will have the opportunity to partner with leaders across different teams to drive strong outcomes and build great products.

Required Skills:

Data Scientist, Messenger Responsibilities:

  1. Work with large and complex data sets to solve a wide array of challenging problems using different analytical and statistical approaches.

  2. Apply technical expertise with quantitative analysis, experimentation, data mining, and the presentation of data to develop strategies for our products that serve billions of people and hundreds of millions of businesses.

  3. Identify and measure success of product efforts through goal setting, forecasting, and monitoring of key product metrics to understand trends.

  4. Define, understand, and test opportunities and levers to improve the product, and drive roadmaps through your insights and recommendations.

  5. Partner with Product, Engineering, and cross-functional teams to inform, influence, support, and execute product strategy and investment decisions.

Minimum Qualifications:

Minimum Qualifications:

  1. Bachelor's degree in Mathematics, Statistics, a relevant technical field, or equivalent practical experience.

  2. 8+ years of experience in Product Data Science, including in depth experience with experimentation.

  3. Experience with data querying languages (e.g. SQL), scripting languages (e.g. Python), and/or statistical/mathematical software (e.g. R)

  4. Experience with predictive modeling, machine learning, and experimentation/causal inference methods.

  5. Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.

Preferred Qualifications:

Preferred Qualifications:

  1. Masters or Ph.D. Degree in a quantitative field.

Public Compensation:

$206,000/year to $281,000/year + bonus + equity + benefits

Industry: Internet

Equal Opportunity:

Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.

Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@fb.com.

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