Research Scientist, Amazon Music - DISCO

Amazon • Culver City, CA

1d

About The Position

Amazon Music is an immersive audio entertainment service that deepens
connections between fans, artists, and creators. From personalized music
playlists to exclusive podcasts, concert livestreams to artist merch, Amazon
Music is innovating at some of the most exciting intersections of music and
culture. We offer experiences that serve all listeners with our different tiers
of service: Prime members get access to all the music in shuffle mode, and top
ad-free podcasts, included with their membership; customers can upgrade to
Amazon Music Unlimited for unlimited, on-demand access to 100 million songs,
including millions in HD, Ultra HD, and spatial audio; and anyone can listen for
free by downloading the Amazon Music app or via Alexa-enabled devices. Join us
for the opportunity to influence how Amazon Music engages fans, artists, and
creators on a global scale.

We are seeking a highly skilled and analytical Research Scientist. You will play
an integral part in the measurement and optimization of Amazon Music marketing
activities. You will have the opportunity to work with a rich marketing dataset
together with the marketing managers. This role will focus on developing and
implementing causal models and randomized controlled trials to assess marketing
effectiveness and inform strategic decision-making. This role is suitable for
candidates with strong background in causal inference, statistical analysis, and
data-driven problem-solving, with the ability to translate complex data into
actionable insights. As a key member of our team, you will work closely with
cross-functional partners to optimize marketing strategies and drive business
growth.

Requirements

• 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

Nice To Haves

• 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

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.

Benefits

• health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
• 401(k) matching
• paid time off
• parental leave

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level