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Junior Data Analyst

Capgemini

New York, New York, United StatesOn Site

Original Job Summary

About the Role

Capgemini is seeking a detail-oriented and analytical Junior Data Analyst to join its growing data team. In this entry-level position, you will support strategic decision-making by collecting, cleaning, analyzing, and visualizing data.

Responsibilities

  • Gather and clean large datasets from various sources.
  • Conduct exploratory data analysis to identify trends and insights.
  • Build dashboards and visualizations to effectively communicate findings.
  • Collaborate with cross-functional teams on data-driven projects.
  • Document processes and maintain data integrity across projects.

Required Skills

  • Bachelor’s degree in Data Science, Statistics, Computer Science, or a related field.
  • Proficiency in Excel and at least one programming language (Python, R, or SQL).
  • Familiarity with data visualization tools such as Tableau or Power BI.
  • Strong analytical, problem-solving, communication, and organizational skills.
  • A keen eagerness to learn and grow in a fast-paced environment.

Life at Capgemini

Capgemini offers flexible work arrangements along with a comprehensive benefits package including healthcare, paid time off, parental leave, financial well-being programs, mentoring, and more. The company is committed to diversity and inclusion and provides equal opportunities for all employees.

Key skills/competency

  • Data Analysis
  • Data Cleaning
  • Exploratory Analysis
  • Dashboarding
  • Data Visualization
  • Excel
  • Python
  • SQL
  • Tableau
  • Cross-functional Collaboration

How to Get Hired at Capgemini

🎯 Tips for Getting Hired

  • Customize your resume: Tailor skills and experiences to data analysis.
  • Highlight technical skills: Emphasize Excel, Python, SQL, and Tableau expertise.
  • Prepare for interviews: Practice data-driven problem-solving questions.
  • Research Capgemini: Understand their projects, values, and culture.

📝 Interview Preparation Advice

Technical Preparation

Practice Python scripting and SQL queries.
Review Excel data manipulation techniques.
Familiarize with Tableau dashboard creation.
Study data cleaning and exploratory analysis basics.

Behavioral Questions

Describe a time you solved data issues.
Explain teamwork in past projects.
Demonstrate handling tight deadlines.
Share a learning experience from feedback.