Analytics

Job Summary

As a Data Analyst, you will be responsible for generating leads, analyzing campaign performance, conducting A/B testing, and uncovering actionable insights to drive business growth. This role requires a strategic thinker with a winning attitude who is eager to explore new methodologies to enhance campaign performance.

Role and Responsibilities / หน้าที่ความรับผิดชอบ

1. Lead Generation and Customer Acquisition:
   • Identify new customer acquisition opportunities through data-driven insights.
   • Develop strategies to cross-sell products and services to existing customers.
   • Collaborate with marketing and sales teams to optimize lead generation efforts.
2. Data Analysis:
   • Analyze campaign performance to identify trends, patterns, and areas for improvement.
   • Provide actionable insights and recommendations based on data analysis to optimize marketing efforts.
   • Perform ad-hoc analysis to support business needs and strategic initiatives.
3. A/B Testing for Campaign Enhancement:
   • Design and execute A/B tests to evaluate the effectiveness of different campaign strategies.
   • Analyze test results to identify winning strategies and improve future campaigns.
   • Collaborate with stakeholders to implement data-driven improvements.

Qualifications / คุณสมบัติ

• 0 to 3 years of professional experience as a Data Analyst, preferably within marketing or customer acquisition.
• Proficiency in Python, PySpark, and SQL for large-scale data processing.
• Hand-on experience with A/B testing and campaign performance optimization.
• Strong analytical and problem-solving skills
• Good communication and interpersonal skills to effectively interact with cross-functional team

Specific knowledge and skill / ความรู้เฉพาะตำแหน่ง

1. Winning Attitude:
   • Eager to logically explore and implement new methodologies to improve campaign performance.
   • Proactive and innovative mindset to drive continuous improvement.
   • Strong problem-solving skills and a results-driven approach.
2. Technical Proficiency:
   • Proficient in data analysis tools such as PySpark, Python, SQL.
   • Strong understanding of statistical methods and data modeling.
3. Collaboration and Communication:
   • Excellent communication skills to effectively present insights to stakeholders.
   • Ability to work cross-functionally with marketing, sales, and product teams.
   • Strong organizational skills and attention to detail.
4. Solid understanding of financial industry.