Data AnalystFull-time

Job highlights

• Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Economics, or Mathematics; strong knowledge of Excel, SQL, and data manipulation; experience with visualization tools like Power BI or Tableau
• Collect, clean, and analyze large datasets; prepare dashboards and reports; identify trends and actionable insights; collaborate with business teams for data-driven solutions

Job match score

Early Applicant

Keyskills

Location

Work Experience

Job description

Overview

We are seeking a detail-oriented Data Analyst to collect, process, analyze, and interpret data to support business decisions. The ideal candidate should have strong analytical skills, proficiency in data tools, and the ability to communicate insights clearly to stakeholders.

Key Responsibilities

• Collect, clean, and analyze large datasets from multiple sources.
• Prepare dashboards, reports, and visualizations to support decision-making.
• Identify trends, patterns, and actionable insights.
• Work closely with business teams to understand requirements and deliver data-driven solutions.
• Build automated reports and improve existing reporting processes.
• Develop and maintain data documentation, KPIs, and performance metrics.
• Ensure data accuracy, quality, and consistency across systems.
• Use statistical methods to interpret data and support forecasting.
• Collaborate with data engineers and product teams for data improvements.

Required Skills

• Strong knowledge of Excel, SQL, and data manipulation.
• Experience with visualization tools such as Power BI, Tableau, or Looker.
• Proficiency in Python or R for data analysis (optional but preferred).
• Understanding of data cleaning, wrangling, and ETL concepts.
• Knowledge of statistics, KPIs, and business metrics.
• Familiarity with databases (PostgreSQL, MySQL, etc.).
• Good problem-solving and analytical thinking skills.
• Strong communication and presentation abilities.

Preferred Qualifications (Optional)

• Experience with cloud data tools (AWS, Azure, GCP).
• Exposure to big data tools like Spark or Hadoop.
• Knowledge of machine learning basics (regression, clustering, etc.).
• Experience with API integrations for data extraction.

Education

• Bachelors or Master’s degree in Data Science, Statistics, Computer Science, Economics, Mathematics, or related fields.