Decision Scientist, Facebook Reality Labs
Oculus

Job Info

The Facebook Reality Labs Marketing decision science team is responsible for driving world-class marketing measurement solutions to maximize FRL products' business growth. The Decision Science team provides insightful analytics on overall marketing performance so we can better connect our users to FRL products. This role will work cross-functionally with marketing, product, data engineering, and research teams to provide insightful analytics and make business recommendations. We are seeking a talented analytics professional who thrives at the intersection of data, purchase behavior, marketing, product, and engineering. The ideal candidate will have a strong technical and analytical background, as well as an intense hunger to make a significant business impact by owning and driving business outcomes. Strong time management and communication skills are critical.Typical projects will include planning and designing advanced marketing experimentations such as RCT, geo-based testing, and optimizing channel performance through targeting, creative optimization and intra channel levers to maximize marketing efficiency, as well as driving insights that can lead to new ways to market to our users.

<ul><li>Partner with marketing, research, and product organizations to scope, design, execute, measure, and improve the impact of our marketing efforts of our business</li><li>Translate data insights into actions and recommendations that will drive user growth and engagement while improving marketing effectiveness</li><li>Expertise in advanced experimentation methods such as randomized trial, network experiments, geo-based testing, cross over experiments, synthetic control to measure marketing's impact globally, and across our suite of AR/VR products (e.g., Oculus, Portal, etc.)</li><li>Identify, design and test optimization methods to improve marketing performance across digital channels as well as linear TV to maximize FRL product growth</li><li>Develop quantitative analysis, tools, ad hoc reports, and models to support marketing decision making. Analysis areas might include (but not limited to): acquisition, retention, lifetime value, targeting, messaging, promotions, usage and engagement</li><li>Produce data visualization such as charts, infographic, and dashboards to communicate findings and actionable recommendations to internal stakeholders clearly and effectively</li></ul>

<ul><li>A degree in economics, operations research, mathematics, statistics, engineering, psychology, or another field with quantitative roots and demands</li><li>4+ years of experience in data analysis, data science, decision science, or similar quantitative fields, applying experimentation methods to test various hypotheses for customer segmentation, user growth, and outbound marketing campaign evaluation</li><li>Experience finding and manipulating data to build data sets</li><li>Experience with statistical modeling and data analysis experience (e.g. significance testing, regression modeling, sampling theory, etc.)</li><li>Experience using R or Python or a similar scripting language for statistical modeling</li><li>Experience with SQL, Hive, Presto, Hadoop, or other data querying languages</li><li>Communication skills and stakeholder management. Experience translating quantitative findings into actionable insights and influence business decisions</li></ul>

<ul><li>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</li><li>Management consulting experience or a similar career requiring one to present data-driven insights to business audiences</li><li>Experience developing data pipelines</li><li>Experience writing production code for automated models</li><li>Experience using open-source statistical packages such as Dplyr, Rstudio, NumPy, Pandas</li><li>Basic experience or basic understanding of machine learning, data mining, and natural language processing</li></ul>

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