Data Analyst at Pharma Ethics

Job Description

• The Data Analyst is responsible for collecting, analyzing, and interpreting data to support strategic decision-making within the organization.
• This role involves working with large datasets, creating meaningful reports, and collaborating with cross-functional teams to uncover insights and trends.

Key Responsibilities
Data Collection and Cleaning:

• Collect and compile data from various sources, ensuring data accuracy and integrity.
• Clean and preprocess data to prepare it for analysis.

Data Analysis:

• Perform exploratory data analysis to identify trends, patterns, and anomalies.
• Conduct statistical analysis and data modeling to extract actionable insights.

Report Generation:

• Create and maintain reports, dashboards, and visualizations to communicate key findings to stakeholders.
• Develop automated reporting systems for regular data updates.

Data Interpretation:

• Translate complex data into understandable and actionable insights for non-technical stakeholders.
• Provide data-driven recommendations to support decision-making.

Data Quality Assurance:

• Monitor data quality and integrity, implementing measures to identify and rectify data discrepancies.
• Develop and maintain data quality standards and procedures.

Cross-Functional Collaboration:

• Collaborate with departments across the organization to understand their data needs and provide analytical support.
• Work with IT teams to ensure data accessibility and security.

Continuous Improvement:

• Stay updated on industry trends and emerging technologies in data analysis.
• Identify opportunities to improve data collection and analysis processes.

Qualifications

• Bachelor's Degree in Data Science, Statistics, Computer Science, or a related field.
• Proven experience as a Data Analyst or in a similar role.
• Proficiency in data analysis tools and software (e.g., Python, R, SQL, Excel).
• Strong analytical and problem-solving skills.
• Excellent data visualization and reporting abilities.
• Knowledge of statistical analysis techniques.
• Attention to detail and a commitment to data accuracy.
• Effective communication and presentation skills.
• Ability to work both independently and collaboratively.