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Phd Causal Inference Jobs in Boston, MA (NOW HIRING)

Compass

Lead Data Scientist

Boston, MA · On-site

$175K - $195K/yr

Master's degree or PhD in Computer Science, Statistics, Economics, Mathematics, or a related ... causal inference). * Extensive practical experience architecting solutions using a broad range of ...

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Phd Causal Inference information

See Boston, MA salary details

$43.5K

$133.5K

$193.9K

How much do phd causal inference jobs pay per year?

As of Sep 4, 2026, the average yearly pay for phd causal inference in Boston, MA is $133,549.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,100.00 and $149,900.00 per year, depending on experience, location, and employer.

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 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 are popular job titles related to Phd Causal Inference jobs in Boston, MA?

For Phd Causal Inference jobs in Boston, MA, the most frequently searched job titles are:

What job categories do people searching Phd Causal Inference jobs in Boston, MA look for?

The top searched job categories for Phd Causal Inference jobs in Boston, MA are:

What cities near Boston, MA are hiring for Phd Causal Inference jobs?

Cities near Boston, MA with the most Phd Causal Inference job openings:

Phd Causal Inference jobs near you
Infographic showing various Phd Causal Inference job openings in Boston, MA as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $133,549 per year, or $64.2 per hour.

VP Marketing & Analytics

Staples Advantage Canada

Framingham, MA • On-site

$250 - $380/hr

Other

Posted 5 days ago

Key responsibilities

  • Build and lead the customer and marketing analytics and data science function across Retail and Staples Inc.

  • Develop a unified strategy to ensure data is reliable, accessible, and actionable across the organization.

  • Partner with engineering and technology teams to enhance data infrastructure, pipelines, and reporting capabilities.

Job description

Vice President, Customer and Marketing Data Science & Analytics

The Marketing organization at Staples plays a critical role in driving growth across our B2B, retail, and services businesses. As Staples continues to evolve into a leading workplace solutions platform, our team leverages data, insights, and innovation to create exceptional customer experiences, optimize marketing performance, and support strategic business decisions. We partner closely with leaders across marketing, product, engineering, merchandising, and operations to unlock growth opportunities and deliver measurable business impact.

Role Summary:

Staples is seeking a visionary and hands-on Vice President to lead the Customer and Marketing Data Science and Analytics organization, and set the vision and agenda to power modern, data-driven marketing and personalization. Reporting to the Chief Marketing Officer, this executive leader will define and execute the end-to-end marketing analytics and data science strategy, enabling smarter decision-making, advanced measurement and attribution, and more personalized customer experiences across all customer touchpoints.

This is a highly visible leadership opportunity, and the leader will shape the future of how data drives growth across one of North America's largest workplace solutions providers. The successful candidate will serve as a strategic partner to senior leadership, building scalable analytics and data science capabilities that create meaningful business outcomes and elevate marketing effectiveness.

What you’ll be doing:
  • Build and lead the customer and marketing analytics and data science function across Retail and Staples Inc.
  • Develop a unified strategy that ensures data is reliable, accessible, and actionable across the organization.
  • Partner with engineering and technology teams to enhance data infrastructure, pipelines, and reporting capabilities.
  • Build and scale data science capabilities including marketing measurement and attribution, UX/creative/offertesting, incrementality, causal inference, lead scoring, personalization, and more.
  • Establish scalable reporting frameworks that provide real-time visibility into marketing performance and business outcomes.
  • Transform reporting from simple metrics delivery into actionable business insights and strategic decision making and recommendations.
  • Lead advanced analytics initiatives, including hypothesis-driven analyses that uncover growth opportunities and performance drivers.
  • Collaborate cross-functionally with product, engineering, sales, and business leaders to embed analytics into decision-making processes.
  • Translate complex data findings into compelling narratives and executive-level recommendations.
  • Develop and execute an analytics roadmap that supports business priorities and long-term growth objectives.
  • Drive continuous improvement in marketing ROI, customer engagement, and overall business performance.
  • Serve as a trusted advisor and thought partner to senior leadership on customer, marketing, and growth strategies.
What you bring to the table:
  • Intellectual curiosity, and passion for solving complex business challenges through data, continuous improvement mindset, and winning attitude.
  • Proven experience leading analytics and/or data science functions within complex, data-rich organizations.
  • Demonstrated success building, scaling, or transforming analytics and data science teams and capabilities.
  • Strong knowledge of modern data ecosystems and how data supports marketing strategy and customer growth.
  • Proven ability to translate complex data into clear, actionable insights that influence business strategy and results.
  • Experience partnering effectively with engineering, product, marketing, and business stakeholders.
  • Familiarity with digital technology platforms and customer data environments.
  • Experience operating in digitally native or digitally transformed organizations.
  • Exceptional communication and executive presentation skills with the ability to engage both technical and non-technical audiences.
  • Collaborative leadership style with a low-ego, team-oriented approach.
  • Ability to balance strategic thinking with operational execution in a fast-paced environment.
What’s needed - Basic Qualifications:
  • Bachelor’s degree in analytical or technical field.
  • 15+ years of progressive experience in analytics, data science, or related disciplines.
  • Experience leading analytics transformations and modernizing data science capabilities.
  • Demonstrated success leveraging data and analytics to improve business outcomes.
  • Exceptional communication, stakeholder management, and executive presentation skills.
What’s needed - Preferred Qualifications:
  • Advanced degree (MBA, MS, PhD, or equivalent) in a relevant discipline.
  • Experience supporting both B2B and B2C business models.
  • Experience within retail, eCommerce, distribution, marketplace, or multi-channel businesses.
  • Background in organizations that combine digital and physical customer journeys.
  • Experience with customer segmentation, attribution, personalization, and marketing optimization models.
  • Familiarity with AI-enabled marketing analytics and advanced customer intelligence solutions.
  • Passion for building high-performing teams and fostering a data-driven culture.
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