Job Title:

Data Science Intern (Remote, Summer – 3 Months)

Company:

HIRIST – IT Recruitment Partner (Hiring for a Technology Client)

Location:

Remote

Job Type:

Internship | Remote | 3-month Duration

About the Role:

HIRIST is seeking motivated Data Science Interns for a part-time remote internship with one of our enterprise clients in the tech domain. The selected candidates will contribute to data-driven

business problem-solving alongside professional data teams.

Key Responsibilities:

• Assist in data preprocessing and basic analytics.
• Support in developing and validating machine learning models.
• Help visualize key business metrics using dashboards.
• Work under supervision to contribute to active internal data projects.

Requirements:

• Working knowledge of Python and/or SQL.
• Strong interest in data science, statistics, or analytics.
• Good problem-solving and communication skills.

Preferred Qualifications:

• Prior coursework, certification, or personal projects in data analytics.
• Familiarity with libraries like Pandas, Matplotlib, or tools like Excel.
• Understanding of basic machine learning or data visualization concepts.

Internship Details:

• Duration: 3 months
• Hours: 15–20 hours/week (flexible timing)
• Stipend: This is an unpaid internship; however, strong performers may be considered for a stipend or future paid roles.
• Certificate of Completion and Letter of Recommendation based on performance.

Hiring Process:

1. Resume Screening
2. Basic data task
3. Online interview with mentor or team lead
4. Final onboarding through HIRIST

Important Notes:

• This internship is fully remote and does not involve any monetary fees at any stage.
• HIRIST is acting solely as a recruitment partner. The client company details will be disclosed during the interview process due to contractual confidentiality.

Equal Opportunity Statement:

HIRIST values diversity and is committed to creating an inclusive environment for all candidates, irrespective of gender, ethnicity, disability, religion, or background.