Data Analyst

TLA is seeking a detail-oriented and analytical Data Analyst to transform complex data sets into actionable business insights. The ideal candidate will be responsible for the full lifecycle of data analysis, including data collection, cleaning, interpretation, and presentation of findings to stakeholders to drive strategic decision-making across the organization.

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:

While not required, the following certifications are a plus:

· 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)

Requirements

Preferred Certifications and Qualifications:

While not required, the following certifications are a plus:

· 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)