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Summer Causal Inference Jobs (NOW HIRING)

Syracuse University

Business Data Scientist

Syracuse, NY · On-site

$74K - $85K/yr

... summer) Hours may vary based on operational needs. This position requires regular on-campus ... Understanding of causal inference, A/B testing, and experimental design * Ability to validate, tune ...

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How much do summer causal inference jobs pay per hour?

As of Jun 4, 2026, the average hourly pay for summer causal inference in the United States is $17.40, according to ZipRecruiter salary data. Most workers in this role earn between $13.94 and $20.67 per hour, depending on experience, location, and employer.

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

To thrive as a Summer Causal Inference Researcher, you need a solid background in statistics, econometrics, and data analysis, typically supported by coursework or a degree in a quantitative field. Familiarity with statistical programming languages like R or Python and experience using tools such as STATA or MATLAB are often required. Strong problem-solving skills, attention to detail, and the ability to communicate complex concepts clearly are valuable soft skills. These skills and qualities are crucial for accurately identifying causal relationships in data and effectively collaborating within interdisciplinary research teams.

What types of projects and methodologies can I expect to work on as a Summer Causal Inference intern?

As a Summer Causal Inference intern, you'll typically work on projects involving the design and analysis of experiments or observational studies to determine cause-and-effect relationships. You may use methodologies such as propensity score matching, difference-in-differences, instrumental variables, or regression discontinuity designs. Collaboration with data scientists, economists, and business stakeholders is common, as you'll help translate findings into actionable insights. Expect to handle real-world datasets and communicate your results through presentations or reports, gaining valuable experience in both technical and applied aspects of causal inference.

What is a Summer Causal Inference position?

A Summer Causal Inference position is typically a short-term research or internship role focused on applying statistical methods to determine causal relationships between variables, often in fields like economics, public policy, or data science. Individuals in this position work on projects that require designing experiments or analyzing observational data to infer causality rather than just correlation. The role is ideal for students or early-career professionals seeking hands-on experience in causal inference techniques during the summer months.
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Summer Causal Inference jobs near you
Infographic showing various Summer Causal Inference job openings in the United States as of May 2026, with employment types broken down into 2% Locum Tenens, 34% Full Time, 34% Part Time, 2% Nights, and 28% Summer. Highlights an 98% Physical, 1% Hybrid, and 1% Remote job distribution, with an average salary of $36,200 per year, or $17.4 per hour.
Principal Data Scientist, Commercialization

Principal Data Scientist, Commercialization

Ver-Tex

Boston, MA • On-site

$152K - $228K/yr

Other

Medical, Dental, Vision, Retirement, PTO

This job post has expired today. Applications are no longer accepted.

Job description

Principal Scientist

We are looking for a deeply technical, intellectually curious Principal Scientist who is excited about the power of AI and motivated to ship solutions that meaningfully change how commercial teams operate.

You will join a high impact Commercial AI and Data Science team working at the intersection of AI, data engineering, and commercial strategy. The team supports a growing portfolio of production AI applications built on a modern Snowflake and Databricks architecture.

This role is ideal for a hands-on expert who codes, experiments, and delivers AI solutions, and who is eager to become a technical leader in advanced ML and AI methods that push the boundaries of what pharma commercial teams can do.

Key Responsibilities:

Advanced Analytics & AI Delivery

  • Design, develop, and deploy advanced analytical and machine learning solutions to support commercial decision making for hundreds of users across multiple disease areas and modalities.
  • Build and enhance Next Best Action models, including propensity scoring, HCP segmentation, and recommendation engines.
  • Develop patient and HCP analytics to support targeting, activation, and reactivation strategies.
  • Apply causal inference and experimental methods to assess the impact of marketing and field interventions.

AI & Platform Enablement

  • Develop and support production grade AI solutions and decision support tools.
  • Partner with data engineering and platform teams to ensure solutions are scalable, compliant, and production ready within Snowflake and Databricks environments.
  • Contribute to the evolution of reusable analytics and AI frameworks that can be leveraged across brands and disease areas.

Commercial Decision Support

  • Collaborate with commercial, marketing, and field leadership to define business requirements and translate them into scalable solution roadmap.
  • Translate complex analytical outputs into clear, actionable insights for nontechnical stakeholders and senior leadership.
  • Support launch readiness, postlaunch optimization, and ongoing performance management through data driven recommendations.

Leadership & Mentorship

  • Serve as a technical leader within the Commercial AI and Data Science team, setting best practices for modeling, experimentation, and impact measurement.
  • Mentor and coach junior data scientists, contributing to capability development and a strong analytics culture.
  • Promote responsible and ethical use of AI in alignment with Vertex values and governance standards.
Required Education and Experience
  • PhD in a quantitative discipline (e.g., Statistics, Computer Science, Engineering, Applied Mathematics) or Master's degree with significant relevant experience.
  • Principal level: typically, 5+ years of hands-on data science experience.
  • Senior Principal (AD) level: typically, 8+ years of experience with demonstrated leadership and ownership of complex analytics initiatives.
  • Proven experience building and deploying analytical or ML solutions in production environments.
  • For Senior Principal level: experience leading and owning complex projects or products.
  • Experience working with healthcare or life sciences data (e.g., claims, EHR, commercial data) is strongly preferred.
Required Knowledge, Skills, and Abilities
  • Strong proficiency in Python and SQL.
  • Experience with modern machine learning techniques and model lifecycle management.
  • Familiarity with cloud-based data platforms such as Snowflake and/or Databricks.
  • Experience building or productionizing LLM-powered or AI-driven applications (e.g., RAG pipelines, agentic workflows) is a strong plus.
  • Ability to operate effectively in fast-paced, ambiguous environments where decisions are made with clear goals but imperfect data.
  • Strong communication skills, with the ability to convey complex analytical concepts to non-technical audiences.
  • Demonstrated ability to collaborate cross-functionally and influence without authority.

Pay Range: $152,000 - $228,000

Disclosure Statement: The range provided is based on what we believe is a reasonable estimate for the base salary pay range for this job at the time of posting. This role is eligible for an annual bonus and annual equity awards. Some roles may also be eligible for overtime pay, in accordance with federal and state requirements. Actual base salary pay will be based on a number of factors, including skills, competencies, experience, and other job-related factors permitted by law.

At Vertex, our Total Rewards offerings also include inclusive market-leading benefits to meet our employees wherever they are in their career, financial, family, and wellbeing journey while providing flexibility and resources to support their growth and aspirations. From medical, dental, and vision benefits to generous paid time off (including a week-long company shutdown in the Summer and the Winter), educational assistance programs including student loan repayment, a generous commuting subsidy, matching charitable donations, 401(k) and so much more.

Flex Designation: Hybrid-Eligible Or On-Site Eligible

Flex Eligibility Status: In this Hybrid-Eligible role, you can choose to be designated as: 1. Hybrid: work remotely up to two days per week; or select 2. On-Site: work five days per week on-site with ad hoc flexibility.

Note: The Flex status for this position is subject to Vertex's Policy on Flex @ Vertex Program and may be changed at any time.

Company Information

Vertex is a global biotechnology company that invests in scientific innovation.

Vertex is committed to equal employment opportunity and non-discrimination for all employees and qualified applicants without regard to a person's race, color, sex, gender identity or expression, age, religion, national origin, ancestry, ethnicity, disability, veteran status, genetic information, sexual orientation, marital status, or any characteristic protected under applicable law. Vertex is an E-Verify Employer in the United States. Vertex will make reasonable accommodations for qualified individuals with known disabilities, in accordance with applicable law.

Any applicant requiring an accommodation in connection with the hiring process and/or to perform the essential functions of the position for which the applicant has applied should make a request to the recruiter or hiring manager, or contact Talent Acquisition at ApplicationAssistance@vrtx.com

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