Data Research Engineer

Team: Engineering

Location: Taipei

Commitment: Full Time

Workplace Type: hybrid

About us

Gogolook is a leading TrustTech company founded in 2012 and listed on the Taiwan Stock Exchange in 2025 under the stock code 6902. With "Build for Trust" as its core value, the company has expanded its business from Asia to Europe and America. Gogolook’s AI technology is built on the world's largest database of digital scam data, encompassing phone numbers, websites, virtual currency wallet addresses, and other factors.

The company provides diverse anti-scam and fintech services for both consumers and businesses. Its anti-scam offerings include the digital anti-scam app "Whoscall" and a range of enterprise scam prevention solutions in combination with "ScamAdviser."

The Fintech BU empowers consumers through data-driven financial services and inclusive lending: Roo.Cash（袋鼠金融）offers transparent matchmaking for financial products like credit cards, while JUJI（招財麻吉）provides an innovative microloan service for rapid, convenient funding during urgent financial needs.

A foundation member of the Global Anti-Scam Alliance (GASA), Gogolook has also teamed up with a number of institutes such as the Taiwan National Police Agency Criminal Investigation Bureau, the Financial Supervisory Service of South Korea, Thai Royal Police, the Fukuoka city and Shibuya City government, the Philippines Cybercrime Investigation and Coordinating Center, and the Royal Malaysia Police and state government to fight scam, dedicated to creating a "scam-free environment."

Why you should join Gogolook

1. Influential products: What we make are meaningful products that create values for society and defend against frauds.
2. Emphasize self-growth: We encourage technical community activities, subsidize tickets for conferences and workshops so that learning is continuously supported by the company.
3. Unleash your talent: We respect the professional opinions of everyone, encourage team members to discuss with each other, and make awesome products together.
4. Transparent culture: We publicly share the company's information to all, every member can read and feedback, and become a part of participating in the proposal.

• Impact-Driven Architects: We require individuals who are motivated by the challenge of creating meaningful products that defend society against global fraud.
• Relentless Learners: We expect you to take full ownership of your growth by actively participating in technical communities and workshops, representing Gogolook's expertise on the global stage.
• Assertive Experts: We value those who bring their own professional opinions to the table, engaging in rigorous discussion to ensure we build only the most exceptional products.
• Radical Collaborators: You must thrive in a culture of extreme transparency, where you are expected to consume company-wide information and actively participate in shaping our collective future.

• Evaluate product needs for intelligent solutions.
• Propose solutions that use cutting-edge AI.
• Create POCs (Proof of Concepts) to demonstrate viability. Together, ISL and Engineering teams meet both the short and long-term technology needs of the company.

Responsibilities

• Hypothesis Testing: Translate defined product questions into testable statistical hypotheses.
• Experimental Design: Design and execute A/B tests or offline validation experiments.
• Statistical Analysis: Perform hypothesis testing, confidence intervals, and basic effect size and power analysis.
• Dataset Engineering: Prepare datasets for testing and model training — cleaning, filtering, and basic deduplication.
• Data Governance: Ensure dataset relevance, formatting, and compliance with data policies.
• Value Assessment: Estimate the marginal lift of new data sources using established methods.
• Documentation: Clearly document experiment design, assumptions, and results.

Qualifications

• Bachelor's degree in Statistics, Data Science, or related quantitative fields.
• 3–5 years of experience in the related area depending on degree.
• Experience in data or experimental design, specifically in designing and executing A/B tests or offline validation experiments.
• Highly independent and self-motivated, with the ability to manage multiple task items within a team environment.
• Ability to learn from mistakes and a continuous drive to seek self-improvement in new skills and technical knowledge.
• Strong collaborative mindset, acting as a good team player who understands how value is delivered both efficiently and responsively.
• Proactive communicator who takes the initiative to voice concerns regarding technical risks and contributes to the creation and reduction of tech debt.

Preferred Qualifications

• Ability to translate complex technical knowledge into clear business language to align with stakeholders.
• Comfortable working with AI/ML Engineers and Product Managers in a supporting capacity to bridge the gap between research and implementation.

Skills & Competencies

• Familiarity with Python (Pandas, Numpy, Scikit-learn), R, Matlab or Javascript.
• Familiarity with SQL and data analysis.
• Ability to perform hypothesis testing, confidence intervals, basic effect size, and power analysis.
• Disciplined in clearly documenting experiment designs, underlying assumptions, and final results.
• Experience with preparing datasets for training and testing, including cleaning, filtering, and basic deduplication.