Manager

Job Summary

Manager – Data Analyst

SQL

Python

Statistics

Advanced Excel

problem-solving

communication

Key Responsibilities

• Lead the data analysis function to deliver insights that influence product, marketing, finance, or operational strategies.
• Write and optimize complex SQL queries to extract, clean, and transform large datasets.
• Use Python for data wrangling, exploratory analysis, and automation of analytics workflows.
• Apply statistical techniques (e.g., regression analysis, hypothesis testing) to analyze trends, identify patterns, and support business experiments.
• Build and maintain dynamic dashboards, reports, and Excel-based models to support decision-making.
• Collaborate with cross-functional stakeholders to gather requirements, define KPIs, and track performance.
• Present analytical findings to technical and non-technical audiences clearly and effectively.
• Lead and mentor junior analysts, providing guidance on best practices and career development.
• Ensure data integrity and drive improvements in data quality and analytical processes.
  

Required Qualifications:

• Bachelor’s or Master’s degree in Statistics, Mathematics, Computer Science, Economics, or a related field.
• 5–8 years of hands-on experience in data analysis or business analytics.
• Strong proficiency in SQL for querying and manipulating data from complex data structures.
• Advanced knowledge of Python for data analysis and scripting (Pandas, NumPy, etc.).
• Solid understanding of statistical concepts and their practical applications.
• Expertise in Advanced Excel including pivot tables, formulas, and data modeling.
• Demonstrated problem-solving ability with a focus on root cause analysis and solutions.
• Excellent communication skills, with experience conveying complex insights to business leaders.
  

Preferred Qualifications:

• Experience working with BI tools (e.g., Power BI, Tableau, Looker).
• Familiarity with version control (e.g., Git) and data visualization best practices.
• Background in mentoring or managing junior analysts or data teams.
• Exposure to data governance and data quality best practices.