decision scientist

The Marketing team focuses on building Meta’s brand presence by improving user sentiment and product education. Our Marketing team seeks to understand how our users feel about our products so we can help people better understand Meta’s intent and mission and guide our users to key features that can enrich their lives. The Decision Science team provides insightful analytics on consumer perception of the Meta experience as a consultative partner to our Marketing team so we can better connect our users to Meta and our products. We are seeking a talented analytics professional who thrives at the intersection of data, human 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. Marketing Decision Scientist Responsibilities: <ul><li>Partner with our marketing teams to make well-informed decisions backed by product usage data and survey results</li><li>Empathize with Meta products users' attitudes, emotions, and opinions to promote product awareness and meaningful interactions on the platform</li><li>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</li><li>Translate data insights into actions and recommendations that will drive brand sentiment, user growth and engagement, and marketing effectiveness</li><li>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</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>Minimum Qualifications: <ul><li>5+ years of experience with a Bachelors (or 3+ years with Masters) 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</li><li>Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience</li><li>Experience finding, cleaning, and manipulating data to build data sets</li><li>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>Experience communicating with cross-functional stakeholders including brand strategists, marketing researchers, product marketing managers, and engineers</li><li>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.</li><li>Advanced experience with SQL and R or Python </li></ul>Preferred Qualifications: <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><li>Experience with Causal Inference Modeling</li><li>Experience with Multi-Touch Attribution or Media-Mix-Modeling</li><li>Experience with longitudinal time-series prediction modeling </li></ul>About Meta: Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics. 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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