... • MS/PhD in a quantitative discipline (or equivalent advanced experience) • Experience ... causal inference and translating results into business actions • Demonstrated ability to mentor ...
... • MS/PhD in a quantitative discipline (or equivalent advanced experience) • Experience ... causal inference and translating results into business actions • Demonstrated ability to mentor ...
... classification, decision trees, clustering, causal inference) • Experience with data ... PhD) preferred. • Experience working in shared analytics/engineering environments (version ...
... classification, decision trees, clustering, causal inference) • Experience with data ... PhD) preferred. • Experience working in shared analytics/engineering environments (version ...
Required : • Successful applicants must hold a PhD or equivalent degree in the field of data ... causal inference, risk stratification, and precision medicine • Experience in transforming ...
Required : • Successful applicants must hold a PhD or equivalent degree in the field of data ... causal inference, risk stratification, and precision medicine • Experience in transforming ...
Some of the core areas of focus for our team include pricing, online advertising, uplift and long term value modeling, and general causal inference. Search & Discovery ML : The Search and Discovery ...
Some of the core areas of focus for our team include pricing, online advertising, uplift and long term value modeling, and general causal inference. Search & Discovery ML : The Search and Discovery ...
Some of the core areas of focus for our team include pricing, online advertising, uplift and long term value modeling, and general causal inference. Search & Discovery ML : The Search and Discovery ...
Some of the core areas of focus for our team include pricing, online advertising, uplift and long term value modeling, and general causal inference. Search & Discovery ML : The Search and Discovery ...
Some of the core areas of focus for our team include pricing, online advertising, uplift and long term value modeling, and general causal inference. Search & Discovery ML : The Search and Discovery ...
Some of the core areas of focus for our team include pricing, online advertising, uplift and long term value modeling, and general causal inference. Search & Discovery ML : The Search and Discovery ...
Some of the core areas of focus for our team include pricing, online advertising, uplift and long term value modeling, and general causal inference. Search & Discovery ML : The Search and Discovery ...
Some of the core areas of focus for our team include pricing, online advertising, uplift and long term value modeling, and general causal inference. Search & Discovery ML : The Search and Discovery ...
Some of the core areas of focus for our team include pricing, online advertising, uplift and long term value modeling, and general causal inference. Search & Discovery ML : The Search and Discovery ...
Some of the core areas of focus for our team include pricing, online advertising, uplift and long term value modeling, and general causal inference. Search & Discovery ML : The Search and Discovery ...
Some of the core areas of focus for our team include pricing, online advertising, uplift and long term value modeling, and general causal inference. Search & Discovery ML : The Search and Discovery ...
Some of the core areas of focus for our team include pricing, online advertising, uplift and long term value modeling, and general causal inference. Search & Discovery ML : The Search and Discovery ...
MS/PhD in a quantitative discipline (or equivalent advanced experience) * Experience deploying or ... Familiarity with experiment design / causal inference and translating results into business actions
MS/PhD in a quantitative discipline (or equivalent advanced experience) * Experience deploying or ... Familiarity with experiment design / causal inference and translating results into business actions
MS/PhD in a quantitative discipline (or equivalent advanced experience) * Experience deploying or ... Familiarity with experiment design / causal inference and translating results into business actions
MS/PhD in a quantitative discipline (or equivalent advanced experience) * Experience deploying or ... Familiarity with experiment design / causal inference and translating results into business actions
... causal inference) * Experience with data visualization tools (e.g., Tableau, Power BI, or similar ... Advanced degree (MS or PhD) preferred. * Experience working in shared analytics/engineering ...
... causal inference) * Experience with data visualization tools (e.g., Tableau, Power BI, or similar ... Advanced degree (MS or PhD) preferred. * Experience working in shared analytics/engineering ...
... causal inference) * Experience with data visualization tools (e.g., Tableau, Power BI, or similar ... Advanced degree (MS or PhD) preferred. * Experience working in shared analytics/engineering ...
... causal inference) * Experience with data visualization tools (e.g., Tableau, Power BI, or similar ... Advanced degree (MS or PhD) preferred. * Experience working in shared analytics/engineering ...
Phd Causal Inference information
See Tennessee salary details
$36.3K - $47.7K
1% of jobs
$47.7K - $59.2K
0% of jobs
$59.2K - $70.6K
2% of jobs
$70.6K - $82K
7% of jobs
$82K - $93.4K
11% of jobs
$95.3K is the 25th percentile. Wages below this are outliers.
$93.4K - $104.9K
24% of jobs
The median wage is $107.1K / yr.
$104.9K - $116.3K
24% of jobs
$121.8K is the 75th percentile. Wages above this are outliers.
$116.3K - $127.7K
12% of jobs
$127.7K - $139.2K
9% of jobs
$139.2K - $150.6K
2% of jobs
$150.6K - $162K
7% of jobs
$36.3K
$111.6K
$162K
How much do phd causal inference jobs pay per year?
As of Aug 14, 2026, the average yearly pay for phd causal inference in Tennessee is $111,572.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,300.00 and $125,300.00 per year, depending on experience, location, and employer.
What are the key skills and qualifications needed to thrive as a PhD causal inference researcher?
To thrive as a PhD Causal Inference researcher, you need advanced knowledge of statistics, econometrics, and causal modeling, typically supported by a doctoral degree in a quantitative field. Familiarity with statistical programming languages (such as R or Python), specialized software (like STATA or SAS), and experience with experimental or quasi-experimental methods are essential. Strong analytical thinking, attention to detail, and the ability to communicate complex findings clearly make a candidate stand out. These skills ensure rigorous, credible research that can inform policy, product development, or scientific understanding by accurately identifying causal relationships.
What collaborative opportunities can a PhD specializing in causal inference expect within a multidisciplinary research team?
PhD professionals in Causal Inference frequently collaborate with experts from fields such as epidemiology, economics, computer science, and public health. They often work closely with data scientists, subject matter experts, and statisticians to design studies, interpret complex datasets, and develop robust analytical models. This multidisciplinary environment fosters continuous learning and often leads to co-authorship on research publications, participation in grant writing, and involvement in high-impact policy or product decisions. Effective communication and teamwork skills are essential to translate technical findings for diverse audiences and drive actionable insights.
What is a PhD in causal inference?
A PhD in Causal Inference is an advanced research degree focused on understanding and identifying cause-and-effect relationships using statistical and computational methods. Students in this field learn to design studies, analyze data, and develop new methodologies to answer complex causal questions in areas such as social sciences, medicine, economics, and artificial intelligence. Graduates often work in academia, research institutions, or industries where evidence-based decision-making is essential.
What are popular job titles related to Phd Causal Inference jobs in Tennessee?
For Phd Causal Inference jobs in Tennessee, the most frequently searched job titles are:
What job categories do people searching Phd Causal Inference jobs in Tennessee look for?
The top searched job categories for Phd Causal Inference jobs in Tennessee are:
What cities in Tennessee are hiring for Phd Causal Inference jobs?
Cities in Tennessee with the most Phd Causal Inference job openings:
Full-time
Re-posted 9 days ago
Starbucks rating
6.7
Based on 3,618 frontline employees who took The Breakroom Quiz
3rd of 16 rated cafes
Job description
Job Summary:
Starbucks is a company known for celebrating coffee and rich tradition, and they are seeking a Senior/Lead Data Scientist. In this role, you will guide business decisions by building and applying statistical and machine learning approaches to solve high-impact problems.
Responsibilities:
• Develop and apply analytical models (statistical and/or machine learning) to improve decision-making, performance, and customer/partner outcomes.
• Translate business problems into data science solutions by defining approach, sourcing/validating data, and communicating clear recommendations to technical and non-technical stakeholders.
• Operationalize your work by creating repeatable analysis/model pipelines, improving model performance over time, and contributing to shared standards (documentation, version control, reproducibility).
Qualifications:
Required:
• 4+ years in data science, applied analytics, or a closely related field
• BA/BS in a quantitative field (or equivalent practical experience)
• Proficiency with Python or R and SQL
Preferred:
• MS/PhD in a quantitative discipline (or equivalent advanced experience)
• Experience deploying or maintaining models in production environments (monitoring, retraining, performance measurement)
• Experience with cloud analytics platforms (e.g., AWS or Azure) and/or distributed computing (e.g., Spark)
• Familiarity with experiment design / causal inference and translating results into business actions
• Demonstrated ability to mentor others and influence cross-functional partners toward adoption
Company:
Starbucks is a restaurant chain that serves handcrafted ready-to-drink beverages, including coffee, tea, juices, and snack food items. Founded in 1971, the company is headquartered in Seattle, USA, with a team of 10001+ employees. The company is currently Late Stage.
Starbucks is a company known for celebrating coffee and rich tradition, and they are seeking a Senior/Lead Data Scientist. In this role, you will guide business decisions by building and applying statistical and machine learning approaches to solve high-impact problems.
Responsibilities:
• Develop and apply analytical models (statistical and/or machine learning) to improve decision-making, performance, and customer/partner outcomes.
• Translate business problems into data science solutions by defining approach, sourcing/validating data, and communicating clear recommendations to technical and non-technical stakeholders.
• Operationalize your work by creating repeatable analysis/model pipelines, improving model performance over time, and contributing to shared standards (documentation, version control, reproducibility).
Qualifications:
Required:
• 4+ years in data science, applied analytics, or a closely related field
• BA/BS in a quantitative field (or equivalent practical experience)
• Proficiency with Python or R and SQL
Preferred:
• MS/PhD in a quantitative discipline (or equivalent advanced experience)
• Experience deploying or maintaining models in production environments (monitoring, retraining, performance measurement)
• Experience with cloud analytics platforms (e.g., AWS or Azure) and/or distributed computing (e.g., Spark)
• Familiarity with experiment design / causal inference and translating results into business actions
• Demonstrated ability to mentor others and influence cross-functional partners toward adoption
Company:
Starbucks is a restaurant chain that serves handcrafted ready-to-drink beverages, including coffee, tea, juices, and snack food items. Founded in 1971, the company is headquartered in Seattle, USA, with a team of 10001+ employees. The company is currently Late Stage.
What Starbucks employees say
Pay
Benefits
Hours and flexibility
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