Data Analytics Internship Program

3 days ago


Stockholm, Stockholm, Sweden Ededge Groups Full time

Ededge Groups

A Leader in Ed-Tech Innovation

We at Ededge Groups are committed to providing unparalleled training programs that foster growth and development in the tech industry. Our aim is to empower individuals with the skills and expertise needed to excel in their chosen careers.

About the Opportunity

This internship offers a unique chance for a Data Analyst Trainee to work alongside our experienced data science team. As part of our team, you will contribute to data management, analysis, and modeling tasks, refining your skills in data visualization and machine learning.

Key Tasks

  1. Collaborate with our data science team to gather, refine, and analyze vast datasets, honing your skills in data preprocessing and visualization.
  2. Implement machine learning and data mining techniques to extract valuable insights from complex datasets, including Excel interface structures.
  3. Use Python programming for Exploratory Data Analysis (EDA) in real-world business scenarios, with a focus on financial risk analysis.
  4. Design and optimize statistical models using advanced modeling technologies like no-code databases and data mining.
  5. Work with a diverse team to develop machine learning pipelines for applications across commerce, finance, and procurement.
  6. Engage with stakeholders to understand business needs, develop hypotheses, and assess strategies using T-tests.
  7. Solve complex problems and create innovative solutions by leveraging modeling technologies like bike share systems.
  8. Leverage advanced analytical techniques using tools like Tableau.
  9. Present findings and methodologies through effective reports and presentations.

Qualifications

  1. Demonstrate strong analytical and problem-solving skills.
  2. Pursuing a degree that reflects a dedication to lifelong learning and professional growth.
  3. Exhibit excellent communication and teamwork abilities.
  4. Proven ability to work independently and remotely.


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