【AstraZeneca】【CET】Associate Principal AI Scientist (Activity optimization lead), Commercial Advanced Analytics, Customer Experience & IT job opportunity at AstraZeneca.



DateMore Than 30 Days Ago bot
AstraZeneca 【AstraZeneca】【CET】Associate Principal AI Scientist (Activity optimization lead), Commercial Advanced Analytics, Customer Experience & IT
Experience: 5-years
Pattern: full-time
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Commercial Advanced Analytics, Customer Experience & IT

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degreeAssociate
loacation Japan - Osaka, Japan
loacation Japan - Osaka....Japan

職務内容 Job Description The Associate Principal AI Scientist (Activity optimization lead) will direct the application of sophisticated quantitative expertise in advanced mathematical disciplines to develop innovative data science solutions. The role will drive the application of foundational and cutting-edge techniques to manipulate and process structured and unstructured data, in combination with business domain knowledge, to develop and apply advanced modelling algorithms (e.g. classification, regression, clustering, NLP, image analysis, graph theory and more) to generate business and scientific insights. They likely coordinate the creation, maintenance and/or improvement of advanced AI models for ongoing and ad hoc review and analysis. The role will work autonomously with limited direct supervision from senior team members. Will provide coaching, task management and support to Associate AI Scientists promoting best practice across multiple domains, and/or stakeholder groups. Requirements 経験 Experience <必須 Mandatory> •    Leading cross-functional analysis projects communicating with both business and IT infrastructure teams. •    Managing project schedule and outcome quality. •    Prioritizing detailed tasks to handle multiple projects with limited resources. •    Designing appropriate approach that resolves complex business issue. •    Multi-person model development using CI/CD (GitHub, Codecommit etc.) <歓迎 Nice to have> •    Stakeholder’s expectation management to maximize benefit for both stakeholders and team members. •    Business communication and document preparations in both Japanese and English languages. •    Managing customer expectations for projects involving multiple stakeholders. •    Willingness of pushing AZKK’s business by accelerating data-driven decision making. 資格 License <必須 Mandatory> •    Bachelors Degree or equivalent number of years of experience in Computer Science or a related quantitative discipline. •    At least 5 year of project experience as leader of analysts using machine learning technology. <歓迎 Nice to have> •    Masters or PhD in computer science or related quantitative discipline. •    At least 5 years of experience in pharma industry or consulting farm. 能力 Skill-set <必須 Mandatory> •    Basic SQL based data extraction. •    Develop Python based ML models using Scikit-Learn, Keras (or Tensorflow), PyTorch, PyG, and other related libraries. •    Ability to create documents to clearly explain complex architecture without using language for specialist. •    Providing Excel based data aggregation. •    Understanding business needs and objectives properly. •    Explaining complex analysis to non-analytical personnel. <歓迎 Nice to have> •    Model deployment by use of SageMaker pipeline. •    Good cocommunication and logical thinking skill. •    Eagerness to absorb new, cutting-edge methods. 語学 Languages <必須 Mandatory> 日本語 Japanese:Business 英語 English:Business 勤務地 Osaka キャリアレベル E Date Posted 19-9月-2025 Closing Date AstraZeneca embraces diversity and equality of opportunity.  We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills.  We believe that the more inclusive we are, the better our work will be.  We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics.  We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorization and employment eligibility verification requirements.

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