Tokyo, Japan
Live, first seen by us 61 days agoAppier's Ad Cloud handles millions of bid requests per second, and that number keeps climbing.
Your job is to find those levers in the data.
Mine campaign, bidding and user data for the biggest performance opportunities
Dig into root causes when metrics shift or contradict each other
Design, run and read high-volume A/B tests on live campaigns
Make ship or no-ship calls on experiment results
Build metric frameworks, datasets and dashboards for stakeholders
Appier's Ad Cloud handles millions of bid requests per second, and that number keeps climbing. Behind every request is a chain of decisions: how much to bid, what to recommend, which creative to show, how fast the system responds. Each one is a lever on campaign performance, and at this scale a 1% improvement is enormous.
Your job is to find those levers in the data. You will turn campaign, auction, and user-behavior data into insights about where the next performance gain is, prove it with rigorous A/B testing, and drive the change across the organization. This is not a back-office role. You will work hand-in-hand with ML scientists, engineers, product managers, and the operations team, and you are expected to set the agenda with data and push until the improvement shows up in live campaigns.
Mine campaign, bidding, and user data to identify the highest-leverage opportunities to improve online campaign performance
When performance shifts or metrics contradict each other, dig until you understand the real mechanism, not just the correlation.
Design, run, and read a high volume of A/B tests on live campaigns.
make clear ship / no-ship calls
Define metric frameworks, build the datasets and pipelines behind them, and deliver dashboards
3+ years of hands-on experience in data analytics or data science in a product- or performance-driven environment.
Strong statistical foundation in experimental design: hypothesis testing, power analysis, and reading noisy online experiments.
Proficiency in Python and expert-level SQL
hands-on experience processing large-scale data in PySpark or a comparable distributed framework
Working knowledge of machine learning sufficient to collaborate with ML scientists
Appier is an AI-native Agentic AI as a Service (AaaS) company that uses artificial intelligence (AI) to power business decision-making.
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Day 61
Up longer than most. Similar jobs usually come down between day 7 and day 56.
At Appier, jobs usually come down by about day 77.
From 10,204 similar postings that came down, and 10 of Appier’s. Coming down is not always a hire.
15 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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- Strong statistical foundation in experimental design: hypothesis testing, power analysis, and reading noisy online experiments. - Proficiency in Python and expert-level SQL, with hands-on experience processing large-scale data in PySpark or a comparable distributed framework. - Working knowledge of machine learning sufficient to collaborate with ML scientists and evaluate models' real-world impact.
- Experience with causal inference or building experimentation infrastructure. - Experience building dashboards (Looker, Tableau, Metabase, Grafana, Superset, or code-based libraries). - Experience building automated or agentic analytics workflows with LLMs.
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New Data Scientist postings at the employers we follow are down 3% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Scientist, by the work the posting describes.
Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.
Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.
Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.
About Appier
Appier is an AI-native Agentic AI as a Service (AaaS) company that uses artificial intelligence (AI) to power business decision-making. Founded in 2012 with a vision of democratizing AI, Appier’s mission is turning AI into ROI by making software intelligent. Appier now has 17 offices across APAC, Europe and U.S., and is listed on the Tokyo Stock Exchange (Ticker number: 4180). Visit www.appier.com for more information.
About the role
Appier's Ad Cloud handles millions of bid requests per second, and that number keeps climbing. Behind every request is a chain of decisions: how much to bid, what to recommend, which creative to show, how fast the system responds. Each one is a lever on campaign performance, and at this scale a 1% improvement is enormous.
Your job is to find those levers in the data. You will turn campaign, auction, and user-behavior data into insights about where the next performance gain is, prove it with rigorous A/B testing, and drive the change across the organization. This is not a back-office role. You will work hand-in-hand with ML scientists, engineers, product managers, and the operations team, and you are expected to set the agenda with data and push until the improvement shows up in live campaigns.
AI now handles much of the mechanics: writing queries, drafting code, producing charts. What it does not do is decide which question is worth asking, notice that a number does not add up, or keep digging when the first explanation is too convenient. That is the job. We are looking for someone who is relentlessly curious about why, and who cannot leave an unexplained anomaly alone.
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Open to overseas candidates/Visa Support
This position is open to based in Taipei, Taiwan or Tokyo, Japan. For international candidates, Appier's Japan office provides visa sponsorship to ensure a smooth transition to Japan.
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Tokyo, Japan
Working pattern and location restrictions need checking in the full posting.
- Experience building automated or agentic analytics workflows with LLMs. Open to overseas candidates/Visa Support This position is open to based in Taipei, Taiwan or Tokyo, Japan. For international candidates, Appier's Japan office provides visa sponsorship to ensure a smooth transition to Japan. #LI-EZ1