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Senior / Lead Analytics Engineer
Insight Timer
Remote, AUS
Full-time
Senior
Remote
Discovered 2 weeks ago
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About Insight Timer
Imagine a platform which could amplify something as simple as your attendance into deep transformational shifts for humanity. A place where showing up was enough. Where each individual visit combined with millions more to trigger huge waves of health and happiness around the world. What would such a platform look like? Could you even build it? And more importantly, how would you protect it from becoming another Instagram, TikTok or Twitter which magnify the very worst of us.
If we can answer these questions, we believe Insight Timer’s community will emerge as one of the most important companies of the 21st century. A place, not a product, which is capable of reversing the modern day health pandemic by harmonising the human spirit before problems arise. And if we get there, well, the opportunities are endless. Imagine a modern-day renaissance where health, belonging and purpose become the new definitions of happiness for hundreds of millions of people around the world, including you.
And all you need to do is show up.
Key Responsibilities
- A/B test analysis. Analyse and interpret experiments, and turn the results into clear recommendations for the product team. Product and engineering own experiment design and setup, you own reading what happened and why.
- Analytics delivery. Turn questions from the product team and company leaders into clear, useful answers, and prioritise incoming requests so the highest-impact work gets done first.
- Data ingestion, modelling and metrics. Own how data comes in, how it’s modelled, and the metrics people trust, using good software engineering practices to ship clean, documented, well-tested datasets.
- Self-serve and agentic analytics. Build the tooling, semantic layers and agents that let the rest of the company answer their own questions, so analytics scales beyond the team.
- Product and revenue analysis. Dig into behavioural and financial data to find user segments, improve conversion, and understand the consumer life cycle in the app.
- Mentoring and leadership. Help grow the analytics engineering team, set technical direction, and lift the quality of what the team ships. At the Lead level this includes directly mentoring and developing other analytics engineers.
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