This is a high impact role with the opportunities to lead the development of state-of-the-art, scalable models to measure the efficacy and effectiveness of a new marketing channel. In this critical role, you will leverage your deep expertise in causal inference to design and implement robust measurement frameworks that provide actionable insights to drive strategic business decisions.
Key Responsibilities:
- Develop advanced econometric and statistical models to rigorously evaluate the causal incremental impact of marketing campaigns on customer perception and customer behaviors.
- Collaborate cross-functionally with marketing, product, data science and engineering teams to define the measurement strategy and ensure alignment on objectives.
- Leverage large, complex datasets to uncover hidden patterns and trends, extracting meaningful insights that inform marketing optimization and investment decisions.
- Work with engineers, applied scientists and product managers to automate the model in production environment.
- Stay up-to-date with the latest research and methodological advancements in causal inference, causal ML and experiment design to continuously enhance the team's capabilities.
- Effectively communicate analysis findings, recommendations, and their business implications to key stakeholders, including senior leadership.
- Mentor and guide junior economists, fostering a culture of analytical excellence and innovation.
Qualifications:
-Experience applying causal inference techniques, such as double machine learning, synthetic control, difference-in-differences, instrumental variables, and randomized experiments.
- Proven track record of developing and implementing sophisticated, scalable models to measure marketing effectiveness and attribution.
- Expertise in programming languages (e.g., R, Python) and proficiency in working with large, complex datasets.
- Strong problem-solving skills, ability to think critically, and a keen eye for detail.
- Excellent communication and presentation skills, with the ability to translate technical analyses into actionable business insights.
- Experience in a fast-paced, data-driven environment, with the flexibility to adapt to changing business needs.
A day in the life
BASIC QUALIFICATIONS
- PhD in economics or equivalent
- Experience in causal inference modelling.
PREFERRED QUALIFICATIONS
- Experience in building statistical models using R, Python, STATA, or a related software
- Experience of productionizing science models and deploying them to handle high-volume, high-velocity data in a production environment.
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $143,300/year in our lowest geographic market up to $247,600/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.