[Primarily Remote] Data Scientist

＜Summary＞

Position: [Remote main] Data Scientist

Salary: ￥8M～13M

Location: Tokyo

【Company Profile】

To evolve corporate "decision-making mechanisms," we leverage the power of AI and data to provide comprehensive solutions across three key axes: management, business operations, and organizational structure. We are not merely an analytics firm, an advertising agency, or a SaaS vendor; we are a data company dedicated to partnering with ambitious enterprises and seeing projects through to tangible results.

Our business rests on three main pillars:

① Data utilization consulting and analytics support bridging management and operations

We establish consistent decision-making processes between management and frontline operations by formulating and executing DX and data utilization strategies. Through methods such as KPI design, fact-based analysis, BI system development, and funnel breakdown, we drive logical DX initiatives that balance operational intuition with rational analysis.

② Marketing execution and technology implementation support to maximize LTV

We support the entire customer lifecycle—from new customer acquisition to deepening engagement with existing customers—by combining advertising operations, CRM initiatives, and social media strategies with technologies like generative AI and BI tools. We drive sustainable business growth through implementation at the operational level.

③ Organizational strengthening through in-house capability building and training systems

Rather than outsourcing analytics and strategy execution entirely, we aim to enable clients to make decisions based on their own judgment by supporting the in-house adoption of data utilization and tool operations. By enhancing the operational team's ability to work autonomously, we facilitate the transformation of the client's organization over the medium to long term.

Instead of relying on bespoke development from scratch for every client, we utilize a versatile product platform as a foundation to deliver support efficiently and flexibly. We offer an engineering environment where you can lead the design and implementation of "practical AI" and "actionable data infrastructure," leveraging proprietary products such as "BI Suite" and "AI Craft."

【Job description】

At our company, data scientists serve as the bridge between conceptualization and implementation when addressing client challenges.

They go beyond mere model development; by understanding the contexts of management, business operations, and frontline activities, they lead the entire process—from designing how data science can transform the business or operations to executing that vision.

The ultimate goal is not simply to build high-precision models, but to achieve a state where solutions are actually used in the field and deliver tangible results.

It is about continuously defining how data science can transform business and operations, rather than stopping at "model development." That is the role of a data scientist at MBK Digital.

You will address client challenges by designing and driving Proof of Concept (PoC) initiatives using data science and AI technologies, leading the technical aspects from the proposal phase through to project execution.

・Clarifying client challenges and identifying key technical issues

・Selecting optimal technical approaches (e.g., Generative AI/RAG, time-series forecasting, mathematical optimization) and defining requirements based on the challenges

・Establishing accuracy evaluation metrics for LLM applications (RAG, agents, etc.) and building data-driven quality improvement processes

・Designing and executing PoCs centered on data analysis and AI application (including implementation of predictive models and optimization algorithms)

・Collaborating with sales and business teams and participating in proposal presentations (handling the technical component)

・Making technical decisions and coordinating efforts to drive projects forward

・Collaborating with internal analytics and product teams

■ Position Appeal and Expected Career Path

・Gain experience in seeing a PoC through to completion, starting from the initial project phase

・Work closely with the proposal and business sides, rather than being confined to a purely technical role

・Enjoy the autonomy to design solutions and drive progress on challenges that lack a predefined template

・Future career paths include roles such as Senior Data Scientist or a technology-driven Business Development/Product Lead

【Requirements】

・Business-level Japanese proficiency

・Practical experience in data analysis or machine learning

・Experience in at least one of the following:

- Defining accuracy evaluation metrics and improving the quality of LLM applications (e.g., RAG)

- Building predictive models using statistics or machine learning

- Implementing algorithms using mathematical optimization (e.g., combinatorial optimization)

・Experience in formulating and executing hypotheses during PoC or validation phases

・Communication skills capable of explaining technical concepts to non-technical stakeholders

・Experience in analysis and implementation using Python or similar languages

【Conditions】

Employment Type: Permanent

Estimated annual income: ￥8~13M

◆ Working Hours

Flextime system (7.5 hours of actual work; includes a 1-hour break)

Core time applies (11:00 AM – 4:30 PM)

* Wednesdays are designated as recommended in-office days.

* Attendance at the monthly company-wide meeting is generally required in person.

◆ Holidays & Leave

・ Five-day workweek (Saturdays and Sundays off)

・ National holidays

・ Summer leave (5 days between July and September)

・ Year-end and New Year holidays (December 28 – January 4)

・ Annual paid leave (Granted upon joining; additional days awarded based on years of service at previous employers; subject to company policy)

・ Bereavement and special occasion leave

・ Etc.

Probationary Period: Yes (3 months)

Benefits

・ Comprehensive social insurance coverage

・ Full reimbursement of commuting expenses (subject to company policy)

・ Certification acquisition allowance (e.g., IPA certifications, Google certifications)