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【ComEx】Senior machine learning operation specialist, Commercial Advanced Analytics G

Location Osaka, Ōsaka, Japan Job ID R-153882 Date posted 19/01/2023

■Job Description / Capsule

This position is responsible for implementation of machine-learning based analysis outcomes on AWS to provide stable and qualified solution that overcome business challenges.
In the daily work, a person in charged will be collaborating with brand team, IT infrastructure, and data scientists to figure out the best practice of operational solution, and report stakeholders to clarify ‘so what’ of resulting benefits by words ease to understand.
To address highly complex business requirements, it is important not only just to build machine-learning operation flow, but also to understand business contexture and market dynamics behind.

本ポジションでは機械学習ベースで構築された分析結果をクラウド環境 (AWS) 上に実装し、複雑なビジネス課題に対して、意義ある知見を安定的に提供する責務を担っていただきます。
日々の業務においてはブランドチームやIT、データサイエンティストと協業し、オペレーションの観点から最適な手法を提案いただきます。また各部門のステークホルダーに対して、ビジネスとして得られる「So What」についてもクリアにご説明いただきます。

■Typical Accountabilities

•Interpret outcomes generated by advanced modeling, and derive the best practice of system architecture in business as usual
•Contexture complex business issues, specifying bottleneck, and expressing a possible solution in plain language
•Develop and maintain analytics platform to process and analyze a vast amount of data
•Collaborate with various functions (Brand team, IT etc.) to propose and implement solutions to business unit in sales and marketing area
•Work across functions to shape, continuously improve advanced analytics capabilities at AstraZeneca
•Manage ongoing business relationships with data vendors, consultants and selected partners


■ Education, Qualifications, Skills and Experience


•Deployment of analysis outcomes to AWS by utilizing several services 
•Explaining the contents of complex analysis system to non-analytical personnel in a way that is easy to understand, and having an agreement on the course of action while executing a project
•Constructing operation flow toward BAU
•ETL process building by PySpark and their maintenance
•Pipelining scratch-developed Python code on SageMaker Studio
•Data extractions by SQL or other related database management languages
•Translating internal business issues into analytical solution

•Several AWS services to deploy machine learning models
(SageMaker Studio (notebook, pipeline), EMR, Athena, Glue, CI/CD pipeline, ECR)
•Ability to properly understand the business needs and objectives
•Script writing: (Py)Spark, Python, SQL
•Python libraries: pandas, scikit-learn, tensorflow, optuna
•Development of Excel based data aggregation
•Ability to create documents to clearly explain complex architecture

•スクラッチ開発されたPythonコードを、SageMaker Studio上でパイプライン化したことがある

(SageMaker Studio (notebook, pipeline), EMR, Athena, Glue, CI/CD pipeline, ECR)
•コーディング: (Py)Spark, Python, SQL
•Pythonライブラリ: pandas, scikit-learn, tensorflow, optuna


•Working in pharmaceutical industry or consulting farm
•Project management such as data analysis and/or system deployment
•Business communication and documentation in both Japanese and English
•Basic advanced modeling (machine learning)


■Key Stakeholders

<Internal (to AZ or team)>

ComEx SFCE, CEX, IDS, Marketing

<External (to AZ)>

IT Venders

■Career Level


■Work Location


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.

10000157 D CNBI

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