Research Scientist, Amazon Music - DISCO

Key job responsibilities

• Develop Causal Models
• Design, build, and validate causal models to evaluate the impact of marketing campaigns and initiatives. Leverage advanced statistical methods to identify and quantify causal relationships.
• Conduct Randomized Controlled Trials
• Design and implement randomized controlled trials (RCTs) to rigorously test the effectiveness of marketing strategies. Ensure robust experimental design and proper execution to derive credible insights.
• Statistical Analysis and Inference
• Perform complex statistical analyses to interpret data from experiments and observational studies. Use statistical software and programming languages to analyze large datasets and extract meaningful patterns.
• Data-Driven Decision Making
• Collaborate with marketing teams to provide data-driven recommendations that enhance campaign performance and ROI. Present findings and insights to stakeholders in a clear and actionable manner.
• Collaborative Problem Solving
• Work closely with cross-functional teams, including marketing, product, and engineering, to identify key business questions and develop analytical solutions. Foster a culture of data-informed decision-making across the organization.
• Stay Current with Industry Trends
• Keep abreast of the latest developments in data science, causal inference, and marketing analytics. Apply new methodologies and technologies to improve the accuracy and efficiency of marketing measurement.
• Documentation and Reporting
• Maintain comprehensive documentation of models, experiments, and analytical processes. Prepare reports and presentations that effectively communicate complex analyses to non-technical audiences.

Basic Qualifications

• PhD, or Master's degree and 4+ years of quantitative field research experience
• Experience investigating the feasibility of applying scientific principles and concepts to business problems and products
• Experience analyzing both experimental and observational data sets
• Experience in causal modeling like graphical models, causal Bayesian network, potential outcomes, A/B testing, experiments, quasi-experiments, and data science workflows

Preferred Qualifications

• Knowledge of R, MATLAB, Python or similar scripting language
• Experience with agile development
• Experience building web based dashboards using common frameworks
• Experience in machine learning, statistics, and deep learning
• Experience working with data mining on large datasets
• Experience working with cross-functional teams