Product Analytics Lead — Drive Growth & Insights

GudangAda

Kelapa Dua

On-site

IDR 167,400,000 - 334,800,000

Full time

14 days+

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Benefits offered by this job

Personal growth
Huge impact to society
Full WFH during the pandemic

Job summary

GudangAda is seeking Product Analytics professionals at multiple seniority levels to join our data-driven product teams in Indonesia. You will collaborate with product, engineering, research, and design to drive growth, improve data deliverables, and monitor performance metrics.

You will work with data engineers and data scientists to maintain data integrity, analyze large datasets, and design/interpret A/B tests.

Qualifications

  • Bachelor's or Master's in CS, Math, Stats, or Engineering from a reputable university.
  • Fresh graduates and experienced hires can apply.
  • Experience with SQL to perform complex queries.
  • Experience with Metabase, Mixpanel, Tableau, or Power BI for dashboards.
  • Experience with Python or R for scripting.

Responsibilities

  • Collaborate with product, eng, research and design to drive product growth.
  • Coordinate with data engineers and data scientists to maintain data quality.
  • Set up and monitor metrics and tracking specifications for performance.
  • Analyze large data sets to identify trends and opportunities.
  • Conduct quantitative analyses: funnel, impact, cost-benefit, segmentation, forecasting.
  • Design and interpret A/B tests to optimize features.
  • Present findings to stakeholders with clear visuals and stories.

Skills

Strong SQL skills
Data analysis
Analytical thinking
Communication skills

Education

Bachelor's or Master's in a quantitative field

Tools

Metabase
Mixpanel
Tableau
Power BI
Python
R

Job description

GudangAda is seeking Product Analytics professionals at multiple seniority levels to join our data-driven product teams in Indonesia. You will collaborate with product, engineering, research, and design to drive growth, improve data deliverables, and monitor performance metrics.

You will work with data engineers and data scientists to maintain data integrity, analyze large datasets, and design/interpret A/B tests.

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