Data Analyst

Everscale Group

We are seeking a talented Data Analyst, who will be responsible for collecting, analyzing, and interpreting complex data sets to provide valuable insights and support informed decision-making. You will collaborate with cross-functional teams to identify data requirements, design data models, and develop reports and visualizations. This is an exciting opportunity to contribute to data-driven strategies and drive business growth.

  • Collect, clean, and transform raw data from various sources for analysis.
  • Perform data exploration, statistical analysis, and data mining to identify trends, patterns, and insights.
  • Develop and maintain data models and databases to ensure data accuracy and accessibility.
  • Create reports, dashboards, and visualizations to present findings and communicate data-driven insights to stakeholders.
  • Collaborate with cross-functional teams to identify business requirements and define key performance indicators (KPIs).
  • Conduct ad-hoc data analysis and provide recommendations for process improvements and optimizations.
  • Perform data validation and quality assurance to ensure data integrity and reliability.
  • Stay up-to-date with industry trends and best practices in data analysis and data visualization techniques.
  • Collaborate with IT teams to implement data governance and security measures.
  • Bachelor’s degree in Mathematics, Statistics, Computer Science, or a related field.
  • Proven experience as a Data Analyst or similar role.
  • Proficient in SQL and data analysis tools (e.g., Python, R, Excel, Tableau).
  • Strong analytical and problem-solving skills with the ability to work with large and complex datasets.
  • Knowledge of data modeling concepts and database management systems.
  • Excellent communication and presentation skills to effectively communicate insights to both technical and non-technical stakeholders.
  • Attention to detail and the ability to work independently or as part of a team.
  • Familiarity with data visualization best practices and tools.
  • Experience with machine learning and predictive analytics is a plus.

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