---
title: 'Data Scientist, Analytics - Tokyo,Japan. at Appier'
canonical: 'https://feeny.ai/job/data-scientist-analytics-tokyo-japan-appier-tokyo-55tbhp1hk5yz'
type: 'job'
last_seen: '2026-09-07'
---

# Data Scientist, Analytics - Tokyo,Japan. at Appier

- **Company:** Appier
- **Location:** Tokyo, Japan
- **Posted:** 2026-09-04
- **Last confirmed live:** 2026-09-07
- **Apply:** https://job-boards.greenhouse.io/appier/jobs/8179099

## Job description

## 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](http://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.

## What You Will Do

- Find where performance comes from. Mine campaign, bidding, and user data to identify the highest-leverage opportunities to improve online campaign performance, and turn them into testable hypotheses.
- Get to the root cause. When performance shifts or metrics contradict each other, dig until you understand the real mechanism, not just the correlation.
- Drive improvements across functions. Partner with ML scientists on bidding and recommendation algorithms, with product and creative teams on creative serving, with engineering on system improvements, and with operations on how campaigns are run. Your insights set the direction; you follow through until the impact lands in production.
- Own experimentation. Design, run, and read a high volume of A/B tests on live campaigns. Define metrics and guardrails, diagnose noisy results, and make clear ship / no-ship calls.
- Build the foundation and make it visible. Define metric frameworks, build the datasets and pipelines behind them, and deliver dashboards that let stakeholders monitor campaign health and act on findings without waiting for a report.
- Work with AI, not just on it. Use AI assistants and agentic tools throughout your workflow so that the team's analytical throughput keeps growing.

You Will Thrive Here If

- You ask "why" one more time than is comfortable, and you verify what AI (and people) hand you.
- You influence scientists, engineers, PMs, and operations teams without direct authority, and you own an initiative from insight to shipped result.
- You treat AI tools as a daily multiplier, with the judgment to know when their output is wrong.

## About you

[Minimum qualifications]

- 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, 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.
- Demonstrated ability to turn analysis into decisions and communicate clearly with technical and non-technical audiences.
- Fluent English, written and spoken.

[Preferred qualifications]

- Experience in programmatic / digital advertising (RTB, DSP, ad networks) and its core metrics (CTR, CVR, CPA, ROAS, win rate).
- 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.

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

## About Appier

## Company Overview
- **One-liner**: Appier is an AI-native Agentic AI as a Service (AaaS) company that empowers businesses to turn AI into ROI through cutting-edge AdTech and MarTech solutions.
- **Entity Type**: Public (Tokyo Stock Exchange, ticker 4180)
- **Headquarters**: Taipei, Taiwan (with 17 offices globally including San Francisco)
- **Founded**: 2012
- **Founders**: Chih-Han Yu (CEO), Wan-Ling Lee (COO), Ming-Yu Chen (CSO), Chia-Yung Su (CTO), Che-Hsu Chang (CIO)

## Core Business
- **Primary industry**: AI-powered advertising technology (AdTech) and marketing technology (MarTech)
- **Target customers**: B2B – primarily enterprise and SMB businesses seeking AI-driven marketing automation, customer data platforms, and programmatic advertising
- **Mission**: "Making AI Easy" – helping businesses turn Agentic AI into ROI

## Products & Services
- **Ad Cloud**: Performance-driven advertising platform that automates creative testing, audience targeting, and campaign optimization to maximize ROAS.
- **Personalization Cloud**: Cross-channel customer engagement platform that personalizes every touchpoint using real-time AI adaptation (includes AIQUA).
- **Data Cloud (AIRIS)**: AI-powered Customer Data Platform (CDP) that centralizes, segments, and activates data for unified audience intelligence and real-time decision-making.
- **Other tools**: Aictivate (mobile gamer re-engagement), CrossX (advertising solution), BotBonnie (conversational marketing platform), AdCreative.ai (generative AI creative generation).

## Market Standing
- **Valuation/Cap**: Market capitalization not publicly available in the search results; company is listed on the Tokyo Stock Exchange (Prime section since 2025).
- **Key Metrics**: Total funding raised (estimated from disclosed rounds): ~$142M+ (Series A $6M, Series B1 $23M, Series C $33M, Series D $80M). Annual revenue not disclosed.
- **Notable Investors/Partners**: Sequoia Capital, SoftBank Group, LINE Corporation, NAVER, EDBI, AMTD Group, TGVest Capital, HOPU-ARM Innovation Fund, Temasek’s Pavilion Capital, JAFCO Asia/Investment, UMC Capital, TransLink Capital, MediaTek Ventures, Fontaine Capital, UOB Venture Management.
- **Growth Signals**: Expanded from 4-person start-up to 17 offices globally, serves 1,800+ customers, acquired Woopra (2022), BotBonnie, QGraph, Emin, AdCreative.ai; ranked top ROI-driving ad partner by Singular for two consecutive years; moved to TSE Prime listing in 2025.

## Competitive Advantages
- **Deep AI R&D**: 70% of R&D staff hold PhDs or Master’s degrees in AI/Big Data, with 400+ academic publications.
- **Agentic AI Platform**: Autonomous, adaptive agents for advertising, personalization, and data – built on proprietary machine learning, deep learning, and generative AI.
- **Full-funnel coverage**: Combines AdTech and MarTech in a unified AI-native stack.
- **Global footprint with localised expertise**: Strong presence across APAC, Europe, and US enables cross-border scalability.

## Strategic Focus
- **Agentic AI expansion** – further develop autonomous AI agents across advertising, personalization, and data clouds.
- **Global growth** – strengthen presence in US and European markets following recent acquisitions (AdCreative.ai, Woopra).
- **Generative AI innovation** – incorporate generative AI into creative and campaign workflows.
- **Sustainability & governance** – Received “AA” MSCI ESG rating, integrating ESG into operations.

## Why Work Here
- **Culture**: “H-appier” framework – Hungry (ambitious, fearless), Humble (open-minded, adaptive), Happier (direct communication, diversity & inclusion, growth). Strong emphasis on execution excellence and customer centricity.
- **Remote/Hybrid/Office**: 17 offices globally; specific policy not detailed but positions are likely hybrid/office-based depending on role (many engineering jobs listed in San Francisco, Taipei, etc.).
- **Team**: 642 total employees (Built In estimate); engineering roles heavily weighted in AI/ML.
- **Perks & environment**: “Start a career, not a job” – career growth tools, collaborative environment, celebration of wins.

## Sources
1. [appier.com](https://www.appier.com/en/)
2. [appier.com/about](https://www.appier.com/en/about)
3. [appier.com/career](https://www.appier.com/en/about/career/)
4. [greenhouse.io](http://job-boards.greenhouse.io/appier)
5. [builtin.com](https://builtin.com/company/appier)

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