★Matching Algorithm Scientist | HR-Tech Company

• Business Level Japanese Required (N3 OK)

◆ Flextime & Fully Remote Work

◆ Famous Venture Company

◆ Annual salary: 6 million yen - 10 million yen

【About the company】

An HRTech company that develops and provides multiple services targeting various stakeholders in the recruitment domain, including hiring companies, recruiting agencies, and job seekers.

The company aims to achieve the optimal matching between companies and talent through the provision of services such as Applicant Tracking Systems (ATS), reference check tools, and recruitment agency management systems.

【 Job Description】

▼About the Company

The company is an HR Tech firm that develops and provides multiple services targeting various stakeholders in the recruitment domain to achieve optimal matching between companies and talent.

The company offers a diverse portfolio designed to modernize the hiring process, including:

・An Applicant Tracking System (ATS) that accelerates the recruitment of digital talent.

・A "Startup Encyclopedia" for career transitions.

・A Job Opening Management System specifically for recruiting agencies.

・A fully online Reference Check Tool.

As of June 2024, the company's core business has been implemented by over 2,000 organizations, ranging from high-growth IT startups to major companies listed on the Tokyo Stock Exchange Prime Market.

While the company has historically achieved growth as an ATS provider, it has recently shifted toward a "Multi-Product Strategy." This involves solving challenges in the recruitment market from multiple angles through the growth of existing services, the launch of new business ventures, and the expansion of its business scope via M&A.

▼Recruitment Background

Having supported the recruitment activities of thousands of companies to date, the company has accumulated a wealth of data concerning job listings, candidate profiles, and selection processes.

Utilizing this data to scientifically determine "which job and which candidate are the best fit" is the key to significantly enhancing both the efficiency and quality of recruitment.

The Matching Algorithm Scientist is responsible for researching and developing algorithms based on this data. By implementing these mechanisms into the company's products, they play a vital role in expanding a system that optimizes the encounters between companies and talent throughout society.

▼Challenges & Opportunities

・Scientific Approach to Recruitment

The company aims to evolve recruitment—which has traditionally relied heavily on intuition and experience—into a system supported by objective data.

・Identifying Reproducible Success Factors

By holistically analyzing candidate skills and aspirations alongside corporate requirements and culture, the scientist will build a framework to identify and reproduce the factors that drive successful hiring.

・Establishing a New Industry Standard

The goal is to go beyond mere recommendation accuracy by incorporating fairness, transparency, and bias reduction, thereby establishing a new benchmark for the recruitment market.

・Driving Business Expansion

By creating new business opportunities and collaborating with external partners based on core matching technologies, the scientist will serve as a driving force for the company's multi-product strategy.

▼Responsibilities

・Designing and Implementing Matching Models: Analyze the company's proprietary recruitment data to design and implement matching models between job listings and candidates.

・Building Scoring and Recommendation Systems: Develop scoring engines and recommendation systems by utilizing machine learning and statistical modeling.

・Product Implementation and Improvement: Collaborate with product teams to implement and continuously refine algorithms within the company's services.

・Process Design for Ethics and Quality: Design evaluation metrics and verification processes to ensure the fairness and transparency of the algorithms.

・Strategic Growth: In the medium to long term, participate in new business development centered on matching technology and engage in external communication/evangelism of the company's technical findings.

▼Team

You will perform the duties as a member of the Data Strategy Team, working in close coordination and collaboration with business owners, Product Managers (PdMs), and engineers across various departments.

▼Growth & Learning

・High Social Impact and Rich Data: An environment where the scientist can apply algorithms to themes of great social significance, using diverse and large-scale recruitment data built upon a foundation of established Applicant Tracking Systems (ATS).

・Bridge Between Research and Practice: The opportunity to gain experience that balances research and practical application, bridging the gap between research outcomes—such as recommendation systems, natural language processing (NLP), and statistical modeling—and their real-world social implementation.

・Shaping the Future of Recruitment: The chance to go beyond simple analysis to challenge the frontier of "Scientific Recruitment," building the mechanisms that shape business growth and define new standards for how hiring should be.

・Researcher Career Path with Market Influence: Looking ahead, the scientist can lead the company-wide algorithm strategy. There are opportunities for external engagement, such as industry-academia collaboration and presentations at academic conferences, allowing for a career that directly influences the Japanese recruitment market.

【 Requirements】

【Required】

Practical experience in algorithm development using machine learning and statistical modeling

Data analysis and modeling skills using Python, R, and other tools

Ability to understand business challenges and design algorithms suitable for product implementation

Communication skills to engage in constructive discussions with internal and external teams and translate outcomes into product features

【Preferred】

Experience in researching and developing recommendation systems and matching algorithms

Experience designing algorithms with fairness and bias reduction in mind

Experience developing new businesses utilizing large-scale data and disseminating research findings

【Working Time 】

Flextime System

【Welfare】

■Commutation Allowance: Provided (subject to a monthly cap).

■Social Insurance: Fully equipped with comprehensive social insurance.

■Health Checkups: Regular medical examinations provided.

■Smoking Policy: No smoking allowed on the premises (measures to prevent passive smoking).

■Babysitter Subsidy Program: Financial support available for babysitting services.

【Holidays and Vacations】

■Saturday/Sunday/National Holiday

■Annual Paid Leave

■New Year Holiday