As a Senior Data Analyst at MeeOpp, you are our expert in data discovery and connecting data with business processes and implications. You will use your strong data analytical skills to extract, organize and analyze data, and create interactive dashboards to visualize insights and trends to help guide business strategy and decision-making. The role requires a good grasp of data analytics abilities, statistical knowledge, and communication skills to present findings to stakeholders.

Key Responsibilities:

Write SQL queries to extract and transform data from databases and other sources to prepare it for analysis. This includes tasks like joining tables, aggregating data, filtering results, preparing reusable datasets and data governance.
Build & maintain interactive dashboards and visualizations using business intelligence tools eg. Looker, Amplitude etc to provide insights into key metrics and KPIs.
Perform ad-hoc analyses and create reports to answer business questions on the fly. Use SQL and data visualization tools to analyze results and highlight insights.
Monitor and maintain key performance dashboards and reports, updating visualizations and analysis to incorporate new data on an ongoing basis.
Document SQL scripts, analysis, and dashboard logic for re-use and knowledge sharing. Follow coding and documentation standards to ensure consistency.
Work with the engineering team to co-own, maintain and optimize our data warehouse
Collaborate with senior management and other departments to better inform them

Qualifications:

5+ years of relevant experience is preferred
Strong analytical and problem-solving skills - A data analyst needs to be able to analyze large datasets, identify issues, and make data-driven recommendations. They need critical thinking and quantitative skills.
Proficiency with data analytics tools/programming - Data analysts must be skilled with eg. Excel, SQL, Python, R, Tableau, etc to gather, clean, analyze and visualize data.
Statistical and mathematical skills - Having mathematical, statistical, and modeling skills allows a data analyst to apply the right techniques for different types of data analysis tasks. Knowledge of statistics is important.
Communication and presentation abilities - Data analysts need to be able to clearly communicate data insights to stakeholders who may not have an analytics background. Strong writing and presentation skills are key.
Domain knowledge/business acumen - Understanding the industry and business operations allows data analysts to better understand the context behind the data and produce more impactful insights and recommendations.
Curiosity and passion for data - Successful data analysts have an inquisitive mindset and continuously ask questions of the data to discover new trends and insights. A passion for data and learning is important.

Bonus Point:

Experience in Machine Learning data ops or training ML models.

Language requirements:

Proficient in English
Fluent in Mandarin Chinese or Cantonese is a plus

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