Job Description:
About Organization
This role sits at the intersection of AI innovation and business strategy. The Data Scientist will play a central role in developing and deploying AI/ML models, uncovering behavioral insights from large-scale customer and network data, and translating those insights into strategic business outcomes. This position demands both technical depth and strategic thinking, ideal for someone who thrives in fast-moving, data-rich environments and can work independently while collaborating across technical and business teams. This role offers the opportunity to analyze some of Japan's most diverse customer datasets, drive AI-driven insights, and shape how data is used to make smarter, faster decisions across multiple business domains.
Job Duties
The Data Scientist will be responsible for:
Model Development & Deployment: Building, validating, and deploying machine learning and AI models for customer segmentation, churn prediction, and behavioral analysis.
Data Handling & Analysis: Working with large volumes of structured and unstructured data (e.g., customer usage, transactions, geolocation, and network patterns). Identifying patterns, anomalies, and commercial opportunities through advanced statistical and predictive analytics.
Insight Translation & Strategy: Translating analytical outcomes into clear business recommendations that improve acquisition, retention, and monetization strategies. Developing frameworks and dashboards to measure market impact, customer engagement, and shop-level performance.
Collaboration & Improvement: Collaborating with data engineering, product, and marketing teams to operationalize models and insights. Contributing to the continuous improvement of data quality, processes, and automation.
Mentorship: Supporting and mentoring junior analysts as the team expands, ensuring analytical consistency and rigor.
Minimum Qualifications
Experience: 10+ years in data science, advanced analytics, or applied machine/deep learning and AI.
Technical Skills: Strong proficiency in Python, SQL, and ML libraries (Scikit-learn, TensorFlow, PyTorch).
Analytical Expertise: Strong grasp of statistical modeling, causal inference, forecasting, and segmentation techniques.
Data Handling: Proven experience working with large, complex datasets (customer behavior, network, or related).
Communication: Ability to convert data-driven findings into concise narratives and strategic insights for non-technical audiences.
Domain Awareness: Understanding of telecom or digital platform ecosystems, particularly the Japanese market. Japanese work culture or willingness to learn is essential.
Mindset: Independent, detail-oriented, and outcome-driven. Comfortable with ambiguity and capable of navigating it effectively.
Preferred Qualifications
Demonstrated experience linking analytics to tangible business impact (e.g., improved conversion, reduced churn).
Ability to design end-to-end pipelines — from hypothesis and feature design to deployment and validation.
Curiosity to explore new AI/ML techniques and applications that can enhance customer experience or revenue potential.
Strong organizational and presentation skills, with a structured approach to problem-solving.
Experience with big data technologies such as Spark, Hadoop, or cloud environments like GCP/AWS.
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