Meta Data Scientist, Product Analytics - Monetization in Helena, Montana
As a Monetization focused Data Scientist at Meta, you will have the opportunity to help people and businesses make meaningful connections and build premium services across our entire family of applications (Facebook, Instagram, Messenger, WhatsApp, Reality Labs). By applying your technical skills, analytical mindset, and product intuition to one of the richest data sets in the world, you will help define the experiences we build for billions of people and hundreds of millions of businesses around the world, and change the way they connect and communicate. You will collaborate on a wide array of product and business problems with a diverse set of cross-functional partners across Product, Engineering, Research, Data Engineering, Marketing, Sales, Finance and others. You will use data and analysis to identify and solve product development’s biggest challenges. You will influence product strategy and investment decisions with data, be focused on impact, and collaborate with other teams. By joining Meta, you will become part of a world-class analytics community dedicated to skill development and career growth in analytics and beyond.Product leadership: You will use data to shape product development, quantify new opportunities, identify upcoming challenges, and ensure the products we build bring value to people, businesses, and Meta. You will help your partner teams prioritize what to build, set goals, and understand their product’s ecosystem.Analytics: You will guide teams using data and insights. You will focus on developing hypotheses and employ a diverse toolkit of rigorous analytical approaches, different methodologies, frameworks, and technical approaches to test them.Communication and influence: You won’t simply present data, but tell data-driven stories. You will convince and influence your partners using clear insights and recommendations. You will build credibility through structure and clarity, and be a trusted strategic partner.
Data Scientist, Product Analytics - Monetization Responsibilities:
Work with large and complex data sets to solve a wide array of challenging problems using different analytical and statistical approaches.
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.
Identify and measure success of product efforts through goal setting, forecasting, and monitoring of key product metrics to understand trends.
Define, understand, and test opportunities and levers to improve the product, and drive roadmaps through your insights and recommendations.
Partner with Product, Engineering, and cross-functional teams to inform, influence, support, and execute product strategy and investment decisions.
A minimum of 6 years of work experience in analytics (minimum of 4 years with a Ph.D.)
Bachelor's degree in Mathematics, Statistics, a relevant technical field, or equivalent practical experience.
Experience with data querying languages (e.g. SQL), scripting languages (e.g. Python), and/or statistical/mathematical software (e.g. R)
- Masters or Ph.D. Degree in a quantitative field.
$173,000/year to $242,000/year + bonus + equity + benefits
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.
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