Data Analyst

Summary

We are seeking a talented and experienced Data Analyst with 3-5 years of industry experience to join our data-driven team. As a Data Analyst, you will play a key role in collecting, analyzing, and interpreting data to drive insights and support data-informed decision-making across the organization.

Qualifications

• Bachelor's degree in Statistics, Mathematics, Economics, Computer Science, or a related field.
• Proven 3-5 years of experience as a Data Analyst or similar role.
• Strong proficiency in SQL and experience working with relational databases.
• Proficiency in data analysis and visualization tools such as Python (Pandas, NumPy, Matplotlib, Seaborn), R, or Tableau.
• Solid understanding of statistical analysis techniques and concepts (e.g., hypothesis testing, regression analysis, clustering).
• Experience with data cleaning, data wrangling, and data preparation.
• Familiarity with data visualization best practices and tools.
• Strong analytical and problem-solving skills with the ability to interpret and draw insights from complex datasets.
• Strong attention to detail and accuracy in data analysis and reporting.
• Excellent communication and interpersonal skills to effectively collaborate with cross-functional teams.

Responsibilities

• Collaborate with cross-functional teams to understand business requirements and define data analysis goals and objectives.
• Collect, clean, and transform data from various sources, ensuring data accuracy, completeness, and integrity.
• Apply statistical analysis techniques and data mining methods to uncover patterns, trends, and correlations in complex datasets.
• Develop and maintain dashboards, reports, and visualizations to effectively communicate data insights and key findings to stakeholders.
• Conduct exploratory data analysis to identify anomalies, outliers, and areas for further investigation.
• Perform data modeling and create data structures to support reporting and analysis needs.
• Develop and implement data quality assurance processes to ensure data accuracy and reliability.
• Collaborate with data engineers to design and optimize data pipelines and data storage solutions.
• Identify and recommend opportunities for process improvements and data-driven optimizations.
• Stay up-to-date with the latest data analysis techniques, tools, and best practices, and recommend innovative solutions to enhance data analysis capabilities.
• Collaborate with stakeholders to understand their data needs and provide analytical support and insights.
• Effectively communicate complex data findings and insights to non-technical stakeholders.

Additional requirements

• Experience with advanced analytics techniques such as machine learning, predictive modeling, or text mining.
• Familiarity with big data technologies and tools (e.g., Hadoop, Spark).
• Knowledge of data governance principles and data privacy regulations.
• Experience with programming languages such as Python or R for data analysis and automation.
• Familiarity with data querying and transformation tools (e.g., Alteryx, Knime).
• Experience with data visualization libraries such as D3.js or Plotly.
• Understanding of data warehousing concepts and dimensional modeling.