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What is a Remote Causal Inference job?

A Remote Causal Inference job involves using statistical and analytical methods to determine cause-and-effect relationships from data, often for fields like healthcare, social sciences, or business. Professionals in this role work remotely, leveraging tools such as R, Python, or specialized software to analyze experiments, observational studies, or large datasets. Their insights help organizations make data-driven decisions, design better interventions, and accurately measure the impact of policies or treatments. Strong skills in statistics, machine learning, and communication are essential for success in this position.

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

To thrive as a Remote Causal Inference Specialist, you need strong quantitative and statistical skills, a solid background in econometrics or data science, and typically an advanced degree in a related field. Proficiency with statistical programming languages such as R or Python, experience with causal inference frameworks like propensity score matching or instrumental variables, and familiarity with data visualization tools are crucial. Outstanding problem-solving abilities, clear communication, and self-motivation are essential soft skills for working independently and conveying complex results to non-technical stakeholders. These skills enable accurate, actionable insights from data, which drive evidence-based decision-making in remote, collaborative environments.

How does a remote Causal Inference specialist typically collaborate with cross-functional teams, and what tools are commonly used?

As a remote Causal Inference specialist, you’ll frequently work with data scientists, product managers, and engineers to design and interpret experiments, analyze observational data, and provide actionable insights. Collaboration usually happens through regular video meetings, shared documentation, and project management tools. Commonly used platforms include Slack or Microsoft Teams for communication, GitHub for code collaboration, and Jupyter Notebooks or RMarkdown for sharing reproducible analyses. These tools help ensure transparency and maintain strong teamwork despite the remote environment.
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Remote Causal Inference jobs near you
Director of Data Analytics

Director of Data Analytics

Indiana Wesleyan University

Indianapolis, IN • On-site, Remote

Full-time

Posted 4 days ago

Indiana Wesleyan University rating

8.6

Company rating: 8.6 out of 10

Based on 14 frontline employees who took The Breakroom Quiz

51st of 537 rated colleges and universities

Job description

Director of Data Analytics
Job no: 495051
Work type: Administrative (Full Time)
Location: Indianapolis, IN, Marion, IN, Hybrid (2 Office / 3 Remote), Remote (within United States), Other
Categories: Administrative/Professional
Job Title: Director of Data Analytics
Reporting Relationship: VP of Learner Success
Unit: National & Global
Department: Dept. of Learner Success-National & Global
Campus Location: Hybrid Schedule (1 day / month Onsite either at Indianapolis Ed Center or Marion, IN campus; the remaining time fully remote).
Summary of Position: The Director of Data Analytics serves as the Strategic Lead for data-driven retention interventions and intervention science within National & Global. Reporting directly to the Vice President of Learner Success, this individual contributor role is responsible for transforming complex student data from the institutional data lake into validated, causal insights that directly improve persistence and completion outcomes for adult online learners.
This position is distinguished by its focus on establishing causality in retention research. The Director applies advanced statistical approaches to move the division from descriptive dashboards to prescriptive, evidence-based action, functioning as the lead practitioner for "Actionable Analytics."
Duties and Responsibilities
  • Intervention Science and Causal Modeling
    • Leads the application of "gold standard" statistical methodologies to establish the causal efficacy of retention interventions
    • Designs and executes quasi-experimental studies using Propensity Score Matching (PSM) to simulate randomized control trials
    • Employs Survival Analysis (time-to-event modeling) to identify critical "danger zones" within the academic term where students are most likely to disengage
    • Utilizes Multi-level Modeling (MLM) to distinguish between student-level factors and systemic programmatic issues
    • Applies Structural Equation Modeling (SEM) to map relationships between latent psychosocial variables and observed outcomes like GPA and course completion
  • Student Success Intelligence Brief Publication
    • Serves as the primary author and strategist for the "Student Success Intelligence Brief," published every six weeks
    • Translates complex statistical findings into clear, actionable steps for faculty and leadership across the DeVoe School of Business, the School of Education, and the School of Service and Leadership
    • Provides high-level, program-segmented analysis of retention trends and provides "Go/No-Go" recommendations for scaling pilot initiatives
  • Psychosocial Metric Development and Validation
    • Operationalizes the integration of non-cognitive measures (Sense of Belonging, Academic Self-Efficacy, Help-Seeking Orientation) into the institutional data model
    • Develops and validates proprietary predictive scales that combine traditional academic indicators with psychosocial factors
    • Ensures that psychosocial triggers are embedded into CRM case records to enable targeted resource referrals by advisors
  • Data Integration and CRM/AI Collaboration
    • Serves as the primary functional liaison to IT and Salesforce teams to access and integrate data from the institutional data lake
    • Defines data requirements and validates data quality for the "Student Insights Agent" and other Agentic AI workflows
    • Ensures that early alert thresholds and "Next Best Action" prompts in Salesforce are grounded in empirically validated retention science rather than arbitrary rules
  • External Benchmarking and Thought Leadership
    • Benchmarks institutional retention outcomes against national standards for online adult learners (IPEDS, National Student Clearinghouse)
    • Represents the institution at national conferences (e.g., EDUCAUSE, AIR) to contribute to the scholarly conversation on student success science

Qualifications: According to Indiana Wesleyan University employment policy all employees must possess a strong Christian commitment and adhere to the standards outlined in the IWU Community Lifestyle Statement.
Education
  • Required: Master's degree in Data Science, Business Analytics, Statistics, Quantitative Psychology, or a related quantitative field
  • Preferred: Doctoral student (ABD - All But Dissertation) with a focus on causal inference, higher education research, or intervention science

Experience
  • Five or more (5+) years of progressive experience in data science, institutional research, or student success analytics
  • Proven track record of establishing causal relationships in educational or behavioral research
  • Experience working with adult learner populations in online or distance learning environments
  • Experience with CRM platforms (Salesforce Education Cloud strongly preferred)

Required Skills
  • Expert-level proficiency in PSM, Survival Analysis, MLM, and SEM
  • Advanced programming skills in R or Python for data manipulation and modeling
  • Proficiency in SQL and experience querying large, complex educational databases/data lakes
  • Strong ability to translate complex data into "Intelligence Briefs" for non-technical executive audiences

IWU Kingdom Diversity Statement
IWU, in covenant with God's reconciling work and in accordance with the Biblical principles of our historic Wesleyan tradition, commits to build a community that reflects Kingdom diversity. We will foster an intentional environment for living, teaching and learning, which exhibits honor, respect, and dignity. Acknowledging visible or invisible differences, our community authentically values each member's earthly and eternal worth. We refute ignorance and isolation and embrace deliberate and courageous engagement that exhibits Christ's commandment to love all humankind.
LIMITATIONS AND DISCLAIMER
As a religious educational institution operating under the auspices of The Wesleyan Church, Indiana Wesleyan University is permitted and reserves the right to prefer employees on the basis of religion (42 U.S.C., Sections 2000e-1 and 2000e-2).
The above job description is meant to describe the general nature and level of work being performed; it is not intended to be construed as an exhaustive list of all responsibilities, duties and skills required for the position. Employees will be required to follow other job-related instructions and to perform other job-related duties requested by their supervisor in compliance with Federal and State Laws.
Advertised: 15 May 2026 US Eastern Daylight Time
Applications close: 21 Jun 2026 US Eastern Daylight Time
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