Senior Economist, Tech Lead, Amazon

Amazon; Santa Monica (CA); On-site; USD 120,000 - 180,000; Full time

Job summary

An innovative leader is sought to join a dynamic team focused on redefining marketing measurement and optimization. In this role, you will leverage your expertise in econometrics and machine learning to tackle complex business challenges, driving impactful initiatives and collaborating with cross-functional teams. As a hands-on innovator, you'll design cutting-edge models and mentor junior scientists, contributing significantly to the advancement of marketing measurement technology. This role offers a unique opportunity to influence strategic decisions and foster a culture of excellence within a diverse and inclusive workplace. If you are passionate about data-driven solutions and eager to make a measurable impact, this position is perfect for you.

Qualifications

• PhD in economics or equivalent required.
• Experience in analytics and applied economics preferred.

Responsibilities

• Design and implement production-ready causal ML models.
• Mentor junior scientists and establish technical best practices.

Skills

Causal Inference Models

Analytical Problem Solving

Machine Learning

Statistical Modeling

Education

PhD in Economics

Tools

R

Python

STATA

Job description

Job ID: 2883176 | Amazon.com Services LLC

Amazon's Global XCM organization (Cross-Category, Cross-Channel Marketing) is looking for a talented Tech Lead Senior Economist who is interested in solving one of the most challenging business problems in marketing measurement and optimization, and developing cutting-edge ML models. Working with our team of data scientists, applied scientists, research scientists, and economists, this leader will help redefine scalable marketing measurement and optimization.

XCM’s mission is to be the most culturally and contextually aware, creatively breakthrough, and measurably effective marketing organization in the world. In this role, you will be a technical leader in econometric research with significant scope, impact, and high visibility. You will lead strategic measurement and optimization science initiatives in collaboration with external science teams, and the development and deployment of measurement and real-time predictive and optimization science models. As a successful Economist, you are an analytical problem solver who enjoys diving into data, leads problem solving, guides the development of new frameworks, writes code, is excited about investigations and algorithms, and can credibly interface between technical teams and business stakeholders. You are an expert in causal inference models to solve business problems. You are a hands-on innovator who can contribute to advancing marketing measurement technology and push the limits on what’s scientifically possible with a razor-sharp focus on measurable customer and business impact. You will also coach and guide junior scientists in the team to grow the team’s talent and scale the impact of your work.

Key job responsibilities

1. Design and implement production-ready causal machine learning models to solve complex measurement and optimization challenges
2. Partner with cross-functional science teams to drive innovative high-impact initiatives
3. Collaborate with key stakeholders to develop strategic roadmaps and ensure successful project execution
4. Mentor junior scientists and establish technical best practices for the team

BASIC QUALIFICATIONS

- PhD in economics or equivalent

PREFERRED QUALIFICATIONS

1. Experience in analytics and applied economics
2. Experience in developing and executing an analytic vision to solve business-relevant problems
3. Experience in building statistical models using R, Python, STATA, or related software
4. Experience in industry, consulting, government, or academic research

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.