Senior Data Analyst - Retail

Senior Data Analyst

Key Responsibilities:

Data Collection:

- Gather, clean, and preprocess data from various sources to ensure its accuracy and reliability.

- Collaborate with internal teams to understand data requirements and source necessary information.

Data Analysis:

- Utilize statistical methods and data analysis tools to identify trends, patterns, and correlations within datasets.

- Perform exploratory data analysis to uncover insights and provide actionable recommendations.

Data Interpretation and Reporting:

- Translate complex data into understandable insights for non-technical stakeholders.

- Prepare and present reports, dashboards, and visualizations to communicate findings effectively.

Quality Assurance:

- Conduct data validation and quality checks to ensure the integrity and reliability of analytical results.

- Implement and maintain data quality standards and best practices.

Data Modeling and Forecasting:

- Develop and implement statistical models for forecasting, trend analysis, and predictive analytics.

- Collaborate with the data science team to enhance and optimize existing models.

Collaboration:

- Work closely with cross-functional teams, including business analysts, IT, and decision-makers, to understand business needs and provide data-driven solutions.

- Participate in meetings and discussions to contribute insights and recommendations based on data analysis.

Continuous Learning:

- Stay updated on industry trends, best practices, and emerging technologies related to data analysis.

- Identify opportunities for process improvement and automation to enhance efficiency.

Qualifications:

- Bachelor's degree in a relevant field (e.g., Statistics, Mathematics, Computer Science, Data Science).

- Proven experience as a Data Analyst or in a similar role.

- Proficiency in data analysis tools such as Python, R, SQL, or others.

- Strong knowledge of statistical methods and data visualization techniques.

- Excellent communication skills and the ability to present complex data findings in a clear and concise manner.

- Attention to detail and problem-solving skills.

Preferred Skills:

- Experience with data warehousing and big data technologies.

- Knowledge of machine learning concepts and algorithms.

- Familiarity with business intelligence tools (e.g., Tableau, Power BI).