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Salary
≈ $14k – $31k per year (Estimated)
Location
In office (Taipei)
Seniority
Middle · 3+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 30, 2026. First seen by Alion on Oct 15, 2026. Hytech scores A on the Alion truth index.

Overview
Company
Impact
Profile match
Hytech is a management consultancy and technology solutions provider specializing in digital transformation and business outsourcing for the fintech sector. Headquartered in Sydney, Australia, the company maintains key regional offices across the Asia-Pacific region, including Kuala Lumpur, Malaysia, and Taipei, Taiwan. Its end-to-end service portfolio spans cloud infrastructure, cybersecurity, custom software and mobile app development, data analytics, and operational support to help enterprises streamline workflows and scale efficiently.

About the role - Data Analyst

As a Data Analyst at Hytech, you will analyze user behavior on financial trading platforms, focusing on app users and their growth journey, including conversion and retention metrics. You will leverage insights from user behavior data to optimize engagement channels-such as push notifications-driving the conversion of registered users into funded, active traders.

(作為 Hytech 的數據分析師,您將負責分析金融交易平台上的用戶行為,專注於應用程式用戶增長過程,包括轉化與留存指標。您將運用數據洞察優化平台渠道,例如透過推播通知,提升用戶參與度,並促使一般用戶轉化為活躍交易者)

身為團隊的一份子您將負責

1. Develop, implement, and maintain leading analytical systems to solve complex problems and build simplified frameworks.

(開發、實施並維護領先的分析系統,以解決複雜問題並建立簡化框架)

2. Analyze complex datasets to identify growth trends and opportunities.

(分析複雜數據集,識別增長趨勢與商機)

3. Evaluate organizational methodologies and provide source-to-target mapping and information model specification documents for datasets.

(評估組織方法,提供數據集的來源到目標映射,以及資訊模型規範文件)

4. Create best-practice reports based on data cleansing, analysis, and visualization.

(基於數據清理、分析與可視化,建立最佳實踐報告)

5. Assess the efficiency, issues, and inaccuracies of internal systems, and establish and maintain standard processes for handling, processing, and cleansing data.

(評估內部系統的效率、問題與不準確性,制定並維護數據處理、整理與清理的標準流程)

6. Collaborate directly with management and users to gather requirements, provide status updates, and build strong relationships.

(直接與管理層及內部用戶合作,收集需求、提供狀態更新,並建立穩固的合作關係)

7. Work closely with project/product managers to understand and continuously address their analytical needs, including identifying key metrics and KPIs, and providing actionable insights to relevant decision-makers.

(與專案/產品經理密切合作,了解並持續關注其分析需求,包括識別關鍵指標與 KPI,並向相關決策者提供可行的數據洞察)

8. Proactively analyze data to respond to key stakeholder questions or spontaneous inquiries, focusing on factors driving business performance and investigating and communicating areas for improving efficiency and productivity.

(主動分析數據,回應關鍵問題或突發性需求,關注推動業務績效的因素,並調查與溝通可提升效率與生產力的改進方向)

9. Interpret and analyze data to create and maintain interactive visualizations, integrating various reporting components from multiple data sources.

(解讀與分析數據,建立並維護互動式視覺化報表,整合來自多個數據來源的各類報告元件)

10. Define and implement data acquisition and integration logic, selecting appropriate methodologies and toolsets to ensure optimal scalability and performance within the defined technology stack.

(定義並實施數據獲取與整合邏輯,選擇適當的方法與工具組合,確保解決方案在既定技術架構下達到最佳的可擴展性與效能)

期待您具備的能力與特質

1. With over 3 years of experience as a Data Analyst (or in a similar role) preferred; ability to work independently, proactively learn and solve problems, quickly adapt to new environments, and self-drive growth without relying on external guidance.

(三年以上數據分析或相關實作經驗; 具備獨立作業能力,能夠主動學習並解決問題,快速適應新環境並自我驅動成長)

2. Strong logical thinking and sharp insights into data, able to proactively explore the potential value of data and propose innovative solutions, rather than just following instructions to complete tasks.

(具備數據邏輯思維與敏銳的洞察力,能夠主動探索數據的潛在價值,並提出創新的解決方案)

3. Capable of providing data-driven insights and suggestions, proactively seeking and proposing opportunities to optimize business, rather than passively accepting analytical assignments.

(能提供數據驅動的洞察與見解,主動尋求並提出優化業務的機會)

4. In a fragmented data storage environment, skilled in data integration and cleaning, able to analyze complex data structures and effectively find usable data sources.

(面對資料儲存分散的環境,具備數據整合與清理的能力,能夠分析複雜的資料結構,並有效找到可用的數據來源)

5. Bonus points: Experience with GA4 (Google Analytics 4) or Sensors Data is a significant advantage. Familiarity with such user behavior analysis tools will help you adapt more smoothly to the existing data environment and perform data tracking and analysis more efficiently.

(額外加分項:若具備 #GA4(Google Analytics 4)或 #神策(Sensors Data)的使用經驗,將會是很大的加分項。熟悉這類使用者行為分析工具的您,在適應現有資料環境、進行資料追蹤和分析時,能更加得心應手。

6. Candidates with a background in finance, fintech, e-commerce, or related fields will be preferred.

(額外加分項:具備金融、Fintech、電商或相關領域背景者將優先考慮)

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