Skip to content
← All opportunities

Data Analyst Internship

InternshipRemoteOnline
Apply on TalentCV β†’

Opens the company's own listing β€” Aspirova never mirrors applications.

Sign in to save
Deadline: 14/11/2026

Skills for this role

Skills we detected for this role.

  • Python
  • SQL
  • Git
  • PostgreSQL
  • Machine Learning
  • Pandas
  • NumPy
  • Data Analysis
  • Power BI
  • Tableau
  • Excel
  • Statistics

Opportunity brief

Responsibilities of the Intern:

  • Assist in collecting, cleaning, and structuring large datasets from internal and external sources.
  • Support business and product teams with data-driven insights.
  • Perform exploratory data analysis (EDA) to identify trends, patterns, and anomalies.
  • Contribute to dashboards and reports used by leadership for decision-making.
  • Work with data engineers and developers to improve data quality and reliability.
  • Prepare visualizations that simplify complex information for non-technical stakeholders.
  • Participate in regular standups, sprint planning, and documentation tasks.
  • Support A/B testing, user behavior analysis, and performance metrics tracking.
  • Clean and preprocess raw data using Python, SQL, or analytical tools.
  • Build and maintain dashboards in tools like Power BI, Tableau, or Looker Studio.
  • Write efficient SQL queries to answer business questions.
  • Automate repetitive data tasks (reports, daily metrics).
  • Analyze KPIs such as user engagement, retention, campaign performance.
  • Document datasets, schemas, data flows, and analysis results.
  • Ensure data accuracy, consistency, and security across systems.
  • Collaborate with cross-functional teams (tech, product, growth, marketing).

Requirements:

  • Strong knowledge of Python (Pandas, NumPy) or R for data manipulation.
  • Hands-on SQL experience (PostgreSQL preferred).
  • Understanding of statistics, probability, and analytical concepts.
  • Ability to create charts, dashboards, and reports.
  • Good Excel/Google Sheets skills.
  • Ability to translate data outcomes into insights.
  • Strong attention to detail and problem-solving skills.
  • Knowledge of ETL pipelines and data warehousing concepts.
  • Familiarity with APIs and JSON data structures.
  • Experience with Git, version control, JIRA/Notion, or Agile methodologies.
  • Understanding of machine learning basics (regression, clustering, classification).
  • Knowledge of tools like Matplotlib, Seaborn, Plotly, or Power BI.

More like this

Related opportunities