Remote Data Analysist (Student Position)

Company Description NYCSE is a United States–based company headquartered at 6 S Dean St in Englewood, New Jersey. The organization operates in a dynamic environment that values data-driven decision-making and practical problem solving. Team members collaborate remotely, supporting a range of projects that benefit from strong analytical and technical skills. NYCSE offers student-oriented opportunities that provide exposure to real-world data challenges and professional development. The company promotes a supportive and inclusive work culture for emerging talent.
Role Description This part-time Remote Data Analyst (Student Position) role focuses on supporting data-related projects across the organization. Day-to-day responsibilities include collecting, cleaning, and organizing data from various sources, conducting basic statistical analysis, and building simple data models to help interpret trends and patterns. The role involves preparing clear summaries, charts, and reports that communicate findings to non-technical stakeholders, as well as assisting in maintaining documentation for datasets and analytical processes. The position is fully remote, offering flexible scheduling to accommodate academic commitments while providing hands-on experience with real-world data tasks.
Qualifications
Candidates should possess strong Analytical Skills and foundational Data Analytics abilities.
Candidates should possess basic knowledge of Statistics and practical experience applying statistical concepts.
Candidates should possess skills in Data Modeling and working with structured datasets.
Candidates should possess clear, professional Communication skills for explaining data findings to diverse audiences.
Candidates should ideally be proficient with common data tools (e.g., Excel, Google Sheets, basic SQL or Python) and data visualization tools.
Candidates should be current students in a relevant field such as Data Science, Statistics, Mathematics, Computer Science, Economics, or a related discipline.
Candidates should demonstrate strong attention to detail, the ability to work independently in a remote setting, and good time management skills.
Prior internship or project experience involving data analysis is beneficial but not required.

Work arrangement
Yes