1

Manager Causal Inference Jobs in Redmond, WA (NOW HIRING)

Applied Science Manager, Stores-Ads Science

Seattle, WA ยท On-site

$43K - $59K/yr

We are a team of interdisciplinary scientists who combine causal inference, economic modeling, and machine learning to drive measurable business impact. We are looking for an Applied Science Manager ...

... causal inference and experimental design to make Prime Video the best-in-class digital video ... with data scientists and product managers to integrate these metrics into Prime Video ...

... causal inference and experimental design to make Prime Video the best-in-class digital video ... with data scientists and product managers to integrate these metrics into Prime Video ...

Sr. Economist, Pricing Science

Seattle, WA ยท On-site

$104K - $132K/yr

Provide causal inference guidance on pricing experiment questions as they arise - being the ... managers. BASIC QUALIFICATIONS - PhD in economics or equivalent PREFERRED QUALIFICATIONS ...

We are looking for a Senior Manager, Data Science to lead a team applying advanced data science and ... causal inference, and modern AI can create the greatest impact. * Lead the development of ...

New

Work with senior management, technical and client teams in order to determine data requirements ... Attribution and causal inference (4+ years)

next page

Showing results 1-20

Manager Causal Inference information

See Redmond, WA salary details

$32.5K

$117.1K

$132.2K

How much do manager causal inference jobs pay per year?

As of Jul 14, 2026, the average yearly pay for manager causal inference in Redmond, WA is $117,119.00, according to ZipRecruiter salary data. Most workers in this role earn between $127,700.00 and $130,500.00 per year, depending on experience, location, and employer.

How does a Manager of Causal Inference typically collaborate with cross-functional teams to drive impactful business insights?

Managers of Causal Inference frequently work alongside data scientists, product managers, engineers, and business leaders to design and execute experiments that reveal the true impact of business decisions. They translate complex statistical findings into actionable recommendations, ensuring stakeholders understand both the methodology and implications. Regularly, they lead discussions on experiment design, data collection strategies, and result interpretation, fostering a culture of evidence-based decision-making across the organization.

What does a Manager Causal Inference do?

A Manager Causal Inference leads teams that analyze data to determine cause-and-effect relationships, often in business, healthcare, or technology settings. They design experiments or use statistical methods to understand how different factors influence outcomes, helping organizations make data-driven decisions. This role typically involves managing projects, overseeing analysts or data scientists, and communicating findings to stakeholders. Strong expertise in statistics, data analysis, and leadership is essential for success in this position.

What are the key skills and qualifications needed to thrive as a Manager of Causal Inference, and why are they important?

To thrive as a Manager of Causal Inference, you need a deep understanding of statistics, econometrics, and experimental design, typically supported by an advanced degree in a quantitative field. Proficiency with data analysis tools such as R, Python, SQL, and specialized causal inference libraries, along with experience using data visualization and project management platforms, is crucial. Strong leadership, communication, and critical thinking skills help you effectively guide teams and translate complex findings to stakeholders. These skills ensure rigorous, actionable insights that drive strategic decision-making and organizational impact.

Economists - ML, Industrial Organization or Environmental Economics

Auger

Bellevue, WA โ€ข On-site

Full-time

Posted 17 days ago


Job description

Job Summary:
Auger is an autonomous operating system for supply chains, connecting enterprise systems into a single data layer. The role involves leading the development of causal inference frameworks and economic models to enhance supply chain decision-making and risk forecasting.
Responsibilities:
โ€ข You will design the methodology behind core platform capabilities: estimating causal drivers of delivery performance; modeling the cost and carbon impact of tariff policy changes; forecasting input costs as functions of commodity prices, exchange rates, and macroeconomic conditions; and building scenario simulation tools that quantify tradeoffs across cost, risk, and sustainability.
โ€ข You will work directly with ML engineers to implement your methods in production systems, validate models against real customer data, and iterate based on observed outcomes.
โ€ข Your causal frameworks will inform automated sourcing recommendations, your tariff models will power interactive scenario planning tools, and your carbon accounting methodology will help companies meet important environmental protection goals and regulatory requirements.
Qualifications:
Required:
โ€ข PhD in economics, with coursework in econometrics and causal inference
โ€ข Experience with causal inference methods with ML: DML or causal forests, instrumental variables, regression discontinuity, synthetic control.
โ€ข Strong programming skills in Python; comfort working in production codebases
โ€ข Ability to translate business questions into well-specified causal or economic frameworks
โ€ข Experience with at least one of: policy impact analysis, market structure modeling, carbon/emissions accounting, or trade economics
โ€ข Clear written and verbal communication; ability to explain methodology to engineers, product teams, and business stakeholders
Company:
Auger is a logistics software startup that integrates with inventory management systems to provide insights for supply chain businesses. Founded in 2024, the company is headquartered in Bellevue, USA, with a team of 51-200 employees. The company is currently Growth Stage.