About
Key Responsibilities
Data Collection & Management:
Collect data from primary and secondary sources, and maintain databases and data systems to ensure accuracy and integrity.
Data Cleaning & Preparation:
Clean, filter, and transform raw data to remove inconsistencies and prepare it for analysis, ensuring high data quality.
Statistical Analysis:
Apply appropriate statistical methods and techniques to interpret data, analyze trends, and identify patterns and correlations that provide valuable business insights.
Reporting & Visualization:
Develop and maintain reports, interactive dashboards, and Key Performance Indicators (KPIs) using data visualization tools to communicate findings in an understandable format for non-technical stakeholders.
Problem Solving:
Collaborate with cross-functional teams (e.g., Marketing, Finance, Operations) to understand business requirements, define analytical needs, and provide data-driven recommendations to solve complex problems and improve processes.
Documentation:
Create clear and concise documentation of data sources, analysis processes, and results to ensure reproducibility and transparency.
Process Improvement:
Identify and implement opportunities to automate and streamline data collection and reporting processes for improved efficiency.
Required Skills and Experience
Proficiency in SQL:
Essential for querying and managing data in relational databases, including advanced functions like joins and aggregations.
Strong Excel Skills:
Advanced proficiency with spreadsheet software, including pivot tables, VLOOKUP/INDEX-MATCH, and complex formulas for data manipulation and quick analysis.
Programming Languages:
Experience with statistical programming languages such as
Python
(using libraries like Pandas, NumPy, and Matplotlib) or
R
for complex analysis and automation.
Data Visualization Tools:
Hands-on experience with Business Intelligence (BI) and data visualization platforms (Tableau or
Microsoft Power BI
preferred).
Statistical Knowledge:
Solid understanding of statistical concepts, including hypothesis testing, regression analysis, and A/B testing.
Soft Skills
Analytical and Critical Thinking:
The ability to logically approach complex problems, ask the right questions, and evaluate data objectively.
Communication Skills:
Excellent written and verbal communication skills, with the ability to translate technical findings into clear, compelling narratives for diverse audiences.
Attention to Detail:
Meticulous attention to detail to ensure the accuracy and reliability of data and analysis.
Problem-Solving Abilities:
A proactive mindset to troubleshoot data issues and find innovative solutions.
Collaboration:
Strong interpersonal skills and the ability to work effectively within a team environment and with various stakeholders.
Experience and Education Bachelor’s degree in a quantitative field such as Computer Science, Statistics, Mathematics, Economics, or a related discipline.
Preferred Certifications and Qualifications
Microsoft Certified: Power BI Data Analyst Associate
Google Data Analytics Professional Certificate
Certified Analytics Professional (CAP)
AWS Certified Data Analytics – Specialty
(for roles involving cloud platforms)
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Languages
- English
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