Data Analyst

Job Summary:

The Data Analyst will play a crucial role in extracting meaningful insights from large datasets to inform business decisions across various domains. The ideal candidate possesses a strong passion for big data and analytics and will be responsible for conducting both recurring and ad-hoc analyses to address key business questions. This role requires a solid understanding of data analysis techniques, proficiency in SQL, and the ability to translate complex data into clear and actionable visualizations.

Responsibilities:

- Business Understanding: Develop a deep understanding of the day-to-day challenges and opportunities within the business to identify areas where data-driven insights can provide value.

- Data Compilation and Analysis: Gather, clean, and analyze data from various sources to address specific business issues and questions. This includes data extraction, manipulation, and statistical analysis.

- Recurring Reporting and Analysis: Develop and maintain regular reports and dashboards to track key performance indicators (KPIs) and provide ongoing insights into business performance.

- Ad-hoc Analysis: Conduct in-depth, ad-hoc analyses to investigate specific business problems, explore potential opportunities, and provide data-backed recommendations.

- Data Visualization: Design and develop clear, concise, and impactful data visualizations (charts, graphs, dashboards) to effectively communicate complex data findings to both technical and non-technical audiences.

- Collaboration with Business Users: Partner closely with business stakeholders across different departments to understand their data needs, gather requirements for analysis, and present findings in a clear and understandable manner.

- Data Quality and Integrity: Ensure the accuracy, consistency, and integrity of the data used for analysis and reporting. Identify and troubleshoot data quality issues.

- Documentation: Maintain clear and comprehensive documentation of data sources, methodologies, and analysis processes.

- Continuous Improvement: Stay updated on the latest data analysis techniques, tools, and industry best practices to continuously improve the quality and efficiency of analysis.

Qualifications:

- Education: Bachelor's or Master's degree in Statistics, Applied Mathematics, Data Science, Computer Science with a focus on Data Analysis, Economics, or a related quantitative field, or equivalent practical experience.

- Experience: 1 - 2 years of hands-on experience in a Data Analyst role or similar analytical position.

- SQL Proficiency: Demonstrated proficiency in writing complex SQL queries to extract, manipulate, and analyze data from relational databases.

- Analytical Skills: Strong analytical and problem-solving skills with the ability to interpret data, identify patterns, and draw meaningful conclusions.

- Data Visualization Skills: Experience in creating effective data visualizations using tools such as Tableau, Power BI, Matplotlib, Seaborn, or similar.

- Statistical Knowledge: Solid understanding of basic statistical concepts and techniques (e.g., descriptive statistics, correlation, regression).

- Communication Skills: Excellent written and verbal communication skills, with the ability to explain technical findings to non-technical audiences.

- Business Acumen: A keen interest in understanding business processes and how data can be used to drive improvements.

- Attention to Detail: Strong attention to detail and a commitment to data accuracy.

- Problem-Solving: Ability to approach analytical challenges with a structured and logical mindset.

Preferred Skills:

- Experience with big data platforms and tools (e.g., Hadoop, Spark, Hive).

- Familiarity with scripting languages for data manipulation and analysis (e.g., Python, R).

- Experience with data warehousing concepts and ETL processes.

- Exposure to statistical modeling and machine learning concepts.

- Experience working with specific business domains (e.g., marketing, sales, operations, finance).

- Familiarity with data governance principles.

Personal Attributes:

- Passion for data and its potential to drive business value.

- Curiosity and a desire to explore and understand data.

- Ability to work independently and as part of a team.

- Proactive and self-motivated with a strong work ethic.

- Ability to learn quickly and adapt to new technologies and business requirements. -