> Markdown version of [/jobs/ext/4693905-data-scientist-hybrid-work](https://www.wearedevelopers.com/jobs/ext/4693905-data-scientist-hybrid-work). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist / Hybrid Work - **Company:** Bloomtech Inc. - **Location:** United States (Remote available) - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** A/B Testing, Data Analysis, Cluster Analysis, Continuous Integration, Linux, Github, Integrated Development Environments, Python (Programming Language), Machine Learning, Natural Language Processing, NumPy, Recommender Systems, SQL Databases, Tableau (Software), Feature Engineering, Pytorch, Large Language Models, Generative AI, Scikit Learn, Data Analytics, Machine Learning Operations, Looker Analytics, Docker - **Published:** November 12, 2026 - **Apply:** https://arc.dev/remote-jobs/j/redirect/pyvu4ewbl8 ## About the Role ・言語/ライブラリ: Python, SQL, NumPy, Scikit-learn, PyTorch ・開発環境/ツール: Linux, VS Code, Git/GitHub, Docker, CI/CD (GitHub Actions) ・分析/関連技術: BIツール (Looker, Tableau, Redash等), NLP, LLM, 生成AI (募集要件) (必須要件(Must)), [Must-have] ・4+ years of professional experience in data science, with strong foundational knowledge in machine learning (prediction, classification, regression, clustering) and statistics. ・Proficiency in Python and SQL with clean, maintainable code, and hands-on experience using key libraries (NumPy, Scikit-learn, PyTorch). ・Proven experience leading the full End-to-End ML lifecycle (data exploration, feature engineering, model training/validation, deployment, and production maintenance). ・Practical knowledge of hypothesis testing, offline model evaluation (cross-validation), and A/B testing. ・Hands-on experience in team development using Linux, VS Code, Git/GitHub, Docker, and CI/CD tools. ・Business-level Japanese, and willingness/motivation to handle technical communication in English. [Nice-to-have] ・Experience analyzing unstructured data (text/speech transcripts) and domain knowledge in NLP/text mining/conversation analysis. ・Experience applying LLM / Generative AI to analytical processes. ・Domain knowledge in call centers or customer support operations. ・Experience building and operating BI tools (Looker, Tableau, Redash, etc.). ・Product Management (PdM) experience coming from a data science background. ・Experience communicating in English with internal global teams. ## Description As a Data Scientist / MLE, you will leverage advanced analytics, machine learning, and statistical modeling to solve complex business challenges through a data-driven approach. You will lead the development and operation of core algorithms-such as recommendation engines and ad delivery optimization-that directly drive business growth and product success. * Responsibilities: Leading core algorithm development and data-driven business growth as a Data Scientist / MLE ・Design and implement recommendation engines and personalized ad delivery optimization models using ML/DL, CLV prediction, and customer segmentation. ・Perform data cleansing, preprocessing, and Exploratory Data Analysis (EDA) on large-scale structured and unstructured datasets. ・Define business KPIs and propose actionable data-driven strategies to internal stakeholders and client marketing teams. ・Establish continuous model improvement loops (MLOps) and research/apply cutting-edge technology (NLP, LLM, Generative AI). ・Provide technical leadership in a global team environment, mentor junior members, and establish development standards and documentation culture. [ Technical Environment ] ・Languages/Libraries: Python, SQL, NumPy, Scikit-learn, PyTorch ・Dev Environment/Tools: Linux, VS Code, Git/GitHub, Docker, CI/CD (GitHub Actions) ・Data & Analytics Tools: BI tools (Looker, Tableau, Redash), NLP, LLM, Generative AI