Data Analyst (225-808)

A Data Analyst plays a crucial role in transforming raw data into actionable insights that drive decision-making within an organization. They are responsible for collecting, processing, and analyzing large datasets to identify trends, patterns, and anomalies. This helps in making informed business decisions and optimizing performance. Data Analysts work with various teams and business units to understand their data needs and support them with reports and visualizations. They have strong analytical skills and use tools like SQL, Excel, and statistical software to perform their tasks efficiently. As technology continues to evolve, Data Analysts are increasingly incorporating machine learning techniques and predictive modeling into their work to forecast outcomes and provide a competitive edge. Adaptability and continuous learning are key, as they must stay current with rapidly advancing data processing technologies.

Responsibilities

• Collect, clean, and process large datasets to prepare for analysis.
• Analyze data to identify trends, patterns, and relationships in datasets.
• Collaborate with various departments to understand data needs and deliver solutions.
• Develop reports and dashboards using visualization tools like Tableau or Power BI.
• Create and maintain documentation for data analytics processes and methodologies.
• Use statistical techniques to analyze large datasets and provide insights.
• Design and implement data collection systems and other strategies for efficiency.
• Communicate findings and insights to stakeholders in a comprehensible manner.
• Work with IT to integrate and improve data collection systems.
• Apply machine learning techniques and predictive modeling to aid decision-making.
• Ensure compliance with data protection regulations and secure data handling.
• Engage in continuous professional development and stay informed on industry trends.

Requirements

• Bachelor's degree in Data Science, Computer Science, Statistics, or a related field.
• Proficiency in SQL and experience with data querying languages is essential.
• Solid understanding of data visualization tools such as Power BI or Tableau.
• Strong analytical skills with the ability to interpret complex data sets.
• Experience with statistical packages such as R, SAS, or Python is required.
• Excellent communication skills to present findings to non-technical stakeholders.
• Detail-oriented, with strong organizational skills and time management abilities.
• Familiarity with machine learning frameworks and predictive modeling techniques.
• Ability to work both independently and in a team-oriented environment.
• Knowledge of data privacy and protection laws, such as GDPR, is beneficial.