Data Analyst for Academic Research (Remote, Part-Time or Full-Time)

# **About the Role:**
We are seeking a highly detail-oriented **Data Analyst** to assist with academic research projects. Your primary role will be **cleaning data, performing statistical analyses, creating tables and charts, and helping summarize findings** for academic papers, conference presentations, and grant proposals.
This is a technical, academic-focused position — **not** corporate business reporting.

# **Responsibilities:**
- Organize, clean, and prepare research datasets (survey data, experimental data, secondary data).
- Conduct descriptive and inferential statistical analyses (means, t-tests, regressions, ANOVAs, chi-square, etc.).
- Summarize results clearly using tables, graphs, and short text write-ups.
- Assist with coding open-ended survey responses where needed.
- Review and summarize academic literature when requested.
- Follow academic standards for data integrity and reporting (APA format when applicable).
- Communicate clearly with project lead, providing regular updates on task progress.

# **Qualifications:**
- Proficient with **R** or **Python** for data analysis (comfortable with packages like `pandas`, `statsmodels`, `scikit-learn`, or `ggplot2`).
- Strong understanding of **descriptive and inferential statistics**.
- Comfortable reading and summarizing **academic journal articles**.
- High level of English reading comprehension and technical writing ability.
- Strong organizational skills and **extreme attention to detail**.
- Bachelor's degree (or currently enrolled senior) in **Statistics, Data Science, Psychology, Marketing, Economics, Sociology, or a related field**.

# **Preferred but Not Required:**
- Experience supporting academic research (theses, dissertations, journal articles, etc.).
- Familiarity with academic writing styles (APA, MLA, etc.).
- Experience with survey platforms (Qualtrics, Google Forms) and exporting data.
- Familiarity with citation managers (Mendeley, Zotero).

# **Application Instructions (Important – Please Read Carefully):**

To apply, you **must** follow these exact steps:

1. **Subject Line of Your Email:**
**"Data Analyst for Academic Research - [Your Full Name]"**
Example: `Data Analyst for Academic Research - Maria Santos`

2. **First Line of Your Email:**
In the very first line of your email, answer the following question:
**"Which statistical method do you find most interesting, and why?"**
(Answer in no more than 2–3 sentences.)

3. **Attach Your Resume:**
Please attach your resume in **PDF format** (no Word documents).

4. **Include a Short Cover Letter in the Email Body:**
After answering the first-line question, briefly describe (no more than 150 words):
- Your experience with data analysis or academic research.
- Why you are a strong fit for this role.

5. **Optional Bonus:**
If you have GitHub repos, project portfolios, data visualization samples, or academic research experience, please include links.

? **Important:** If you do not follow these application instructions exactly, your application will be **automatically rejected**.
Attention to detail and ability to follow instructions are essential for this role.

# **Work Hours:**
- Flexible schedule (mostly asynchronous work).
- Occasional check-ins during U.S. Mountain Time hours preferred.

# **Summary:**
This role is ideal for someone who loves academic research, statistical analysis, and turning messy data into clear, publishable results. You do **not** need advanced machine learning skills — a strong foundation in **statistics, careful data handling, and clean communication** is what matters most.