Decision Scientist
Menlo Park, CA
- Partner with our marketing teams to make well-informed decisions backed by product usage data and survey results
- Empathize with Meta products users' attitudes, emotions, and opinions to promote product awareness and meaningful interactions on the platform
- Partner with marketing, research, and product organizations to scope, design, execute, measure, and improve the impact of our marketing efforts on the world and on our business
- Translate data insights into actions and recommendations that will drive brand sentiment, user growth and engagement, and marketing effectiveness
- Develop quantitative analysis, tools, ad hoc reports, and models to support marketing decision making. Analysis areas might include (but not limited to): retention, sentiment, lifetime value, messaging, promotions, usage, and engagement
- Produce data visualization such as charts, infographic, and dashboards to communicate findings and actionable recommendations to internal stakeholders clearly and effectively
- Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
- 5+ years of experience with a Bachelors (or 3+ years with MBA) in data analysis, data science, decision science, or similar quantitative fields, applying experimentation methods to test various hypotheses for customer segmentation, consumer sentiment or perception, and outbound online marketing campaign evaluation
- Experience finding, cleaning, and manipulating data to build data sets
- Statistical modeling and data analysis experience (e.g. significance testing, regression modeling, sampling theory, etc.)
- Experience using R or Python or a similar scripting language for statistical modeling
- Experience with SQL, Hive, Presto, Hadoop, or other data querying languages
- Experience communicating with cross-functional stakeholders including brand strategists, marketing researchers, product marketing managers, and engineers
- An MBA or Master's or Doctorate degree in economics, operational research, mathematics, statistics, engineering, psychology, or another field with strong quantitative roots and demands
- Management consulting experience or a similar career requiring one to present data-driven insights to business audiences
- Experience developing data pipelines
- Experience writing production code for automated models
- Experience using open-source statistical packages such as Dplyr, Rstudio, NumPy, Pandas
- Experience with Causal Inference Modeling
- Experience with longitudinal time-series prediction modeling or other types of predication models
- Basic experience or basic understanding of machine learning, data mining, and natural language processing
Individual pay is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base salary, Meta offers benefits. Learn more about benefits at Meta.
Tags: Causal inference Computer Science Consulting Data analysis Data Mining Data pipelines Data visualization Economics Engineering Hadoop Machine Learning Mathematics NLP NumPy Open Source Pandas Physics Pipelines Python R Research SQL Statistical modeling Statistics Testing VR
Perks/benefits: Career development Equity / stock options Flex vacation Health care Salary bonus
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