Meta - Menlo Park, CA

posted 5 months ago

Full-time
Menlo Park, CA
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About the position

The Creator Marketing team at Meta plays a crucial role in connecting creators with their audiences and facilitating their growth through various tools and features. The Data Scientist in this team will be instrumental in understanding the experiences of creators on Meta's platforms, which is essential for guiding them towards key features and enhancing their overall experience. This position requires a deep understanding of data, human behavior, marketing, product development, and engineering. The Data Scientist will conduct experiments, develop models, and provide insights into the creator base, identifying opportunities and evaluating the effectiveness of marketing strategies. The ideal candidate will thrive in a fast-paced environment, demonstrating a passion for problem-solving and delivering data-driven insights. In this role, the Data Scientist will apply multiple statistical approaches and write elegant, reproducible code to execute analyses. They will leverage large amounts of structured data to gain insights into customer interactions with Meta's products and services. The Data Scientist will proactively identify opportunities to enhance the creator experience across Meta's applications. They will lead the measurement, analysis, and interpretation of results, collaborating with cross-functional teams to identify new opportunities that require modern analytical techniques. Additionally, the Data Scientist will design and execute experiments, such as A/B testing, and communicate insights and recommendations to marketing leads to influence strategic decision-making.

Responsibilities

  • Applies multiple statistical approaches as needed
  • Writes elegant, reproducible code as needed to execute analyses
  • Draws insights from quantitative data and begins to identify deeper-level implications
  • Takes advantage of massive amounts of structured data to understand how customers interact with product and service offerings
  • Proactively identifies opportunities to improve the experience of creators on the Meta family of apps
  • Leads the measurement, analysis, and interpretation of results from data requirement gathering to modeling and recommendations
  • Partners with cross-functional teams to identify new opportunities requiring the use of modern analytical and modeling techniques
  • Designs and executes experiments (e.g., A/B testing, multi-armed bandit)
  • Communicates insights and recommendations to marketing leads and influences strategic decision-making

Requirements

  • 4+ years of experience in a data science capacity in a business strategy, marketing, finance, engineering, or analytics organization
  • 4+ years of experience with data querying and manipulation using SQL, Python, or R
  • Experience with experimental design
  • Experience with data analysis and statistical modeling using the R or Python ecosystems, with packages such as pandas, Statsmodels, Scikit-learn, Tidyverse (dplyr, ggplot2, etc.)
  • Experience with stakeholder communication and presentation skills
  • Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta.

Nice-to-haves

  • An MBA or Master's or Doctorate degree in a quantitative discipline like Math, Statistics, Economics, Computer Science, Physics, Engineering, Operations Research
  • Self-starter, comfortable with ambiguity, experience initiating and driving projects with minimal oversight and guidance
  • Proven track record of leveraging data to deliver business value and present data-driven insights to senior leaders
  • Experience developing data pipelines via SQL and Python-based ETL framework
  • Experience with online marketing and advertising data analysis
  • Experience building cross functional relationships across a variety of functions to launch projects to drive business value
  • Experience communicating with and influencing technical and non-technical audiences (engineers, data scientists, program managers, marketers)
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