Description:

The company is a fintech startup offering a cash-rewards platform called MoMo’s (Money Moments) for consumers, merchants, and gamers.
The Data Scientist will lead investigations into the virtual economy and products using hypothesis-driven insights and experimentation methods.
Responsibilities include designing and implementing data science workflows, communicating complex topics to technical and non-technical stakeholders, and analyzing data using statistical programming languages and SQL.
The role involves mentoring team members, collaborating with cross-functional teams, and developing data visualizations and dashboards to influence business decisions.
Continuous exploration of new ideas and data sources is encouraged to solve ambiguous problems.

Requirements:

A degree in Mathematics, Statistics, Computer Science, or a related field is required.
Candidates should have 5+ years of experience in analytics or data science positions.
Deep understanding of statistical analysis, including hypothesis testing and experimentation, is essential.
Proficiency in statistical programming languages (R, Python, Julia) and SQL is necessary.
Familiarity with data engineering tools like dbt, Spark, and Snowflake is expected.
Strong skills in writing structured and efficient SQL queries for large datasets are required.
Experience in building data visualizations and dashboards with tools like Looker, Tableau, Mixpanel, or similar is a must.
Excellent communication skills for explaining complex topics are needed.
Passion for mentoring team members and fostering growth through teaching is important.
A background in gaming and knowledge of the free-to-play business model is a plus.

Opportunity to work in a vibrant fintech startup environment.
Chance to work with top-tier venture capitalists Play Ventures & F4 Fund.
Engage in rewarding everyday actions through the MoMo’s (Money Moments) cash-rewards platform.
Collaborate with cross-functional teams to drive business outcomes.
Foster a culture of growth through mentoring and knowledge sharing.
Continuous learning and exploration of new ideas and data sources.