TECH-Bilingual Data Scientist_TokyoDev

TECH-Bilingual Data Scientist_TokyoDev 仕事概要 # Job Overview ## About the Position ### Role Overview As a **Senior Data Scientist**, you will leverage advanced analytics, machine learning, and statistical modeling to solve complex business challenges through data-driven approaches. This role requires deep technical expertise to transform data insights into actionable business strategies, as well as strong communication skills to collaborate effectively with cross-functional teams. We welcome candidates with extensive experience in analytics, the IT/technology industry, and cutting-edge AI technologies. ## Key Responsibilities ### Machine Learning for Ad Delivery Optimization Design, develop, and maintain machine learning models that optimize personalized advertising delivery to maximize business outcomes. This includes customer lifetime value (CLV) prediction, multi-channel customer modeling, customer segmentation, and extracting actionable insights from campaign performance. ### Personalization & Recommendation Systems Design and implement recommendation engines using rule-based methods, machine learning, and deep learning techniques to improve user engagement and strengthen brand trust. ### Advanced Customer Segmentation Lead customer behavior analysis using clustering and other advanced segmentation techniques to develop highly personalized strategies that enhance customer engagement and brand value. ### Data Engineering & Exploratory Data Analysis (EDA) Clean, preprocess, and validate large-scale structured and unstructured datasets. Perform exploratory data analysis (EDA) to identify meaningful patterns, ensure data quality, and establish analytical strategies for solving business problems. ### KPI Design & Stakeholder Collaboration Partner with internal teams—including Sales and Customer Success—as well as client marketing teams to define, propose, and communicate business KPIs that are both ambitious and easily understood by non-technical stakeholders. ### Continuous Model Improvement Continuously improve model performance by conducting systematic validation, error analysis, and iterative enhancements to model architectures and feature engineering in order to achieve business KPIs. ### Collaborative Development & Responsible AI Manage production-grade code repositories using GitHub while maintaining best practices in version control and documentation throughout the research and development lifecycle. Ensure compliance with data privacy requirements and responsible AI principles. ### Research & Application of Cutting-Edge AI Technologies Research and implement state-of-the-art AI technologies, including deep learning, natural language processing (NLP), large language models (LLMs), and Generative AI, to solve business challenges and enhance product and brand value. ## Team You will join Mico's **Data & AI Team**. # What We Expect from You As a Senior Data Scientist, you will be expected to: * Lead the entire machine learning lifecycle for core algorithms such as recommendation engines and advertising optimization—from data exploration and feature engineering to model implementation, deployment, and production maintenance. * Continuously improve model accuracy and business value, driving measurable revenue growth and business impact through data-driven decision making. * Partner with business and executive stakeholders to translate business challenges into data-driven solutions, leading KPI definition and strategic initiatives. * Mentor junior team members in both technical and non-technical areas while establishing engineering best practices, documentation standards, and a strong development culture that maximizes overall team performance. # What You'll Gain ## Build Business-Critical AI with Proprietary Data Work with a unique combination of Mico's first-party data and customers' zero-party data to build highly accurate machine learning models. You'll develop AI solutions that directly solve business challenges and create measurable revenue impact. ## End-to-End Production ML & MLOps Experience Gain hands-on experience building and operating production-grade machine learning systems, including feature pipelines, model retraining, monitoring, and MLOps infrastructure for recommendation engines and advertising optimization. ## Drive Business Strategy Through Data Go beyond model development by partnering with business leaders to define KPIs and shape data-driven business strategies that directly influence company growth. ## Global Technical Leadership Take technical ownership within an English-speaking global engineering team while mentoring junior engineers, establishing development standards, and building a strong track record as a globally recognized technical leader. # Career Opportunities ### Technical Lead / Engineering Manager Advance into a leadership role as a Tech Lead or Engineering Manager for Data Science or Machine Learning teams, leveraging your technical expertise and mentoring experience. ### ML Architect / Principal Data Scientist Deepen your expertise in large-scale data processing, advanced MLOps, and cutting-edge AI technologies while shaping company-wide data platforms and machine learning architecture. ### Data Product Manager (PdM) / AI Consultant Expand into product strategy or AI consulting by leveraging your experience in defining business challenges, designing KPIs, and driving data-driven initiatives that accelerate business growth. ### Global AI & Data Leadership Lead large-scale, cross-border AI initiatives by combining strong English communication skills with extensive machine learning expertise, building a career as a global AI leader. 必須スキル # Job Overview ## About the Position ### Role Overview As a **Senior Data Scientist**, you will leverage advanced analytics, machine learning, and statistical modeling to solve complex business challenges through data-driven approaches. This role requires deep technical expertise to transform data insights into actionable business strategies, as well as strong communication skills to collaborate effectively with cross-functional teams. We welcome candidates with extensive experience in analytics, the IT/technology industry, and cutting-edge AI technologies. ## Key Responsibilities ### Machine Learning for Ad Delivery Optimization Design, develop, and maintain machine learning models that optimize personalized advertising delivery to maximize business outcomes. This includes customer lifetime value (CLV) prediction, multi-channel customer modeling, customer segmentation, and extracting actionable insights from campaign performance. ### Personalization & Recommendation Systems Design and implement recommendation engines using rule-based methods, machine learning, and deep learning techniques to improve user engagement and strengthen brand trust. ### Advanced Customer Segmentation Lead customer behavior analysis using clustering and other advanced segmentation techniques to develop highly personalized strategies that enhance customer engagement and brand value. ### Data Engineering & Exploratory Data Analysis (EDA) Clean, preprocess, and validate large-scale structured and unstructured datasets. Perform exploratory data analysis (EDA) to identify meaningful patterns, ensure data quality, and establish analytical strategies for solving business problems. ### KPI Design & Stakeholder Collaboration Partner with internal teams—including Sales and Customer Success—as well as client marketing teams to define, propose, and communicate business KPIs that are both ambitious and easily understood by non-technical stakeholders. ### Continuous Model Improvement Continuously improve model performance by conducting systematic validation, error analysis, and iterative enhancements to model architectures and feature engineering in order to achieve business KPIs. ### Collaborative Development & Responsible AI Manage production-grade code repositories using GitHub while maintaining best practices in version control and documentation throughout the research and development lifecycle. Ensure compliance with data privacy requirements and responsible AI principles. ### Research & Application of Cutting-Edge AI Technologies Research and implement state-of-the-art AI technologies, including deep learning, natural language processing (NLP), large language models (LLMs), and Generative AI, to solve business challenges and enhance product and brand value. ## Team You will join Mico's **Data & AI Team**. # What We Expect from You As a Senior Data Scientist, you will be expected to: * Lead the entire machine learning lifecycle for core algorithms such as recommendation engines and advertising optimization—from data exploration and feature engineering to model implementation, deployment, and production maintenance. * Continuously improve model accuracy and business value, driving measurable revenue growth and business impact through data-driven decision making. * Partner with business and executive stakeholders to translate business challenges into data-driven solutions, leading KPI definition and strategic initiatives. * Mentor junior team members in both technical and non-technical areas while establishing engineering best practices, documentation standards, and a strong development culture that maximizes overall team performance. # What You'll Gain ## Build Business-Critical AI with Proprietary Data Work with a unique combination of Mico's first-party data and customers' zero-party data to build highly accurate machine learning models. You'll develop AI solutions that directly solve business challenges and create measurable revenue impact. ## End-to-End Production ML & MLOps Experience Gain hands-on experience building and operating production-grade machine learning systems, including feature pipelines, model retraining, monitoring, and MLOps infrastructure for recommendation engines and advertising optimization. ## Drive Business Strategy Through Data Go beyond model development by partnering with business leaders to define KPIs and shape data-driven business strategies that directly influence company growth. ## Global Technical Leadership Take technical ownership within an English-speaking global engineering team while mentoring junior engineers, establishing development standards, and building a strong track record as a globally recognized technical leader. # Career Opportunities ### Technical Lead / Engineering Manager Advance into a leadership role as a Tech Lead or Engineering Manager for Data Science or Machine Learning teams, leveraging your technical expertise and mentoring experience. ### ML Architect / Principal Data Scientist Deepen your expertise in large-scale data processing, advanced MLOps, and cutting-edge AI technologies while shaping company-wide data platforms and machine learning architecture. ### Data Product Manager (PdM) / AI Consultant Expand into product strategy or AI consulting by leveraging your experience in defining business challenges, designing KPIs, and driving data-driven initiatives that accelerate business growth. ### Global AI & Data Leadership Lead large-scale, cross-border AI initiatives by combining strong English communication skills with extensive machine learning expertise, building a career as a global AI leader. 歓迎スキル # Preferred Qualifications ## Recommendation Systems Expertise * Hands-on experience designing and developing recommendation systems using techniques such as **Collaborative Filtering**, **Content-Based Filtering**, **Matrix Factorization**, **Neural Collaborative Filtering (NCF)**, **Two-Tower architectures**, and other modern recommendation algorithms. ## Advanced Machine Learning Engineering * Experience with **online inference (online serving)**, model deployment, and production-grade ML workflows, including feature pipelines, model monitoring, retraining, continuous improvement cycles, and MLOps best practices. * Experience designing and developing **microservice architectures** using frameworks such as **FastAPI** or **Flask**. * Experience fine-tuning open-source deep learning models, including embedding models, sequence models, multi-task learning architectures, and other state-of-the-art AI models. * Experience developing and operating **high-QPS (Queries Per Second), low-latency machine learning APIs** in production environments. ## Data Engineering & Orchestration * Experience designing and operating scalable data pipelines using workflow orchestration tools such as **Apache Airflow** or **AWS Step Functions**. * Hands-on experience with streaming and messaging technologies such as **AWS Kinesis** and **Apache Kafka**. * Experience working with distributed computing and large-scale data processing frameworks such as **Apache Hadoop**, **Apache Spark**, or **MPI**. ## Domain Expertise & Business Acumen * Experience working on projects related to **ranking systems**, **search**, **advertising optimization**, **personalization**, or similar data-driven products. * Ability to translate business objectives and domain knowledge into actionable data analysis and data-driven improvement initiatives. * Strong understanding of **user behavior analytics**, **business growth metrics**, and optimization from a business impact perspective. ## Community Involvement & Research * Demonstrated passion for applied machine learning through contributions to **open-source software (OSS)**, published research papers, participation in **Kaggle** or similar competitions, or other meaningful contributions to the machine learning community. 求める人物像 # Who We're Looking For We're looking for someone who: * Can build alignment and collaborate effectively with both internal and external stakeholders across cross-functional teams. * Is able to translate complex data analysis into clear, compelling, and actionable insights for non-technical audiences. * Can transform business challenges into data-driven solutions and approaches, demonstrating persistence and ownership in solving complex problems. * Has excellent time management and organizational skills, with the ability to work independently and proactively drive initiatives to completion. * Is passionate about mentoring and developing junior team members from both technical and non-technical perspectives while fostering a high-performing team culture. * Has a strong desire to stay at the forefront of AI and data science, continuously learning, adopting, and implementing the latest technologies. 応募概要 給与 # Compensation **Annual Salary** **JPY 8,040,000 – 11,000,000** Compensation will be determined based on your experience, skills, and current compensation. **Salary Breakdown** * **Monthly Salary:** JPY 670,000 – 917,000 * **Base Salary:** JPY 495,722 – 678,473 * **Fixed Overtime Allowance (45 hours/month):** JPY 174,278 – 238,527 * Any overtime exceeding 45 hours per month will be compensated separately. **Compensation Structure** * Annual salary paid in **12 equal monthly installments** **Benefits** * Transportation allowance provided in accordance with the company's policy. 勤務地 勤務地は希望に沿って東京・大阪いずれかを選択いただきます。 リモートと出社のハイブリッドで柔軟な働き方をしております。（週1出社推奨） ■大阪拠点 大阪府大阪市北区大深町6番38号 グラングリーン大阪 北館 JAM BASE 5階 JAM-OFFICE 5-A・5-B ■東京拠点 東京都港区北青山 2-14-4 the ARGYLE aoyama 6F WeWorkジアーガイル 雇用形態 正社員 勤務体系 ■勤務時間 9:00～18:00　※休憩1時間含む、時間外労働あり フレックスタイム制（コアタイム10:00～16:00） ※会社規定により、一定のグレード以上の方には裁量労働制が適用されます。 ■休日・休暇 ・土日、祝日 ・年末年始 ・夏季休暇 ・慶弔休暇 ・有給休暇（入社時10日付与、以降勤務期間に応じて付与） ※その他会社規定による休日あり 試用期間 原則3ヶ月　※試用期間中の待遇変更はありません 福利厚生 ・交通費支給（自転車通勤可） ・社用ノートPC貸与 ・社用携帯貸与　※一部職種のみ ・就業開始時間選択制度（2ヶ月ごとに申請可） ・社会保険（健康保険、厚生年金、雇用保険、労災保険） ・ライフヘルス支援休暇 ・健康診断費用負担 ・出産・育児支援制度 ・部活動