Department:Data Analysis
Type:REMOTE
Region:USA
Location:United States
Experience:Mid-Senior level
Estimated Salary:$70,000 - $100,000
Skills:
SQLPYTHONRTABLEAUPOWER BIDATA VISUALIZATIONSTATISTICAL ANALYSISDATA MODELING
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Job Description

Posted on: July 23, 2025

Job Title: Data Analyst

Job Type: Contract

Open to all visa types

Key Responsibilities:

  • Collect, clean, and analyze large datasets from various sources.
  • Develop and maintain dashboards, reports, and data visualizations to present insights to stakeholders.
  • Identify trends, patterns, and correlations within data to drive business strategies.
  • Work closely with cross-functional teams to understand business needs and provide data-driven recommendations.
  • Utilize SQL, Python, R, or other analytical tools to extract and manipulate data efficiently.
  • Ensure data integrity and accuracy by implementing best practices for data governance and validation.
  • Support ad-hoc data requests and provide insights for business improvement.
  • Stay updated with the latest industry trends, tools, and technologies in data analytics.

Required Qualifications:

  • Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.
  • 2+ years of experience in data analysis, business intelligence, or a related role.
  • Proficiency in SQL and experience working with relational databases.
  • Hands-on experience with data visualization tools (Tableau, Power BI, or similar).
  • Strong analytical skills with experience in statistical analysis and data modeling.
  • Proficiency in programming languages such as Python or R for data manipulation and analysis.
  • Excellent communication and presentation skills to translate complex data into actionable insights.
  • Ability to work independently in a remote environment and manage multiple tasks effectively.

Preferred Qualifications:

  • Experience working with cloud-based data warehouses (AWS Redshift, Google BigQuery, or Snowflake).
  • Knowledge of machine learning concepts and predictive analytics.
  • Familiarity with ETL processes and data pipeline development.
  • Experience in a specific industry such as healthcare, finance, e-commerce, or technology.
Originally posted on LinkedIn

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