Data Scientist

Summary

岗位工作地点在青岛。数据科学家将通过使用统计、机器学习和/或人工智能方法对数据进行操作和分析来推动业务洞察力。这将包括在分析之前操作和准备数据（结构化和非结构化），开发高级建模算法，以及以易于理解的方式呈现数据以帮助传递洞察力。

数据可虚假应拥有动手操作经验、计算科学技能、强大的沟通技巧以及在制造和供应链环境中成功应用数据科学的经验。 该职位将大量参与大数据和高级分析，以支持现场数据和系统集成，以实现现场制造数字化转型。

负责先进技术、数字化、自动化的应用场景的引入，支持青岛工厂实现一流的数字化、自动化工厂的愿景。该职位还负责支持精益经理发展精益能力和精益领导力，在青岛工厂培养精益/持续改进文化。

This role is based in Qingdao. The Data Scientist will drive business insight through the manipulation and analysis of data using statistical, machine learning and / or AI methodologies. This will include manipulating and preparing data (structured and unstructured) prior to analysis, the developing advanced modelling algorithms, and presenting data in a comprehensible way to help impart insight.

The data scientist will possess a blend of hands-on operational experience, computational science skills, strong communication skills and experience of successfully applying data science in a manufacturing and supply chain environment. The role will be heavily involved in Big Data and Advanced analytics to support site for data and system integration to enable site manufacturing digital transformation.

This role is responsible for the introduction of advanced, digital, and automated application scenarios, supporting Qingdao site to achieve automation factory vision. This role is also responsible for support lean manager to develop lean capability and lean leadership, embedded lean/continuous improvement culture in Qingdao site .

Responsibilities

作为最终用户参与和支持青岛工厂的项目建设

Support project team to deliver Qingdao pMDI project as end user

参与到项目的不同阶段，作为最终用户提供有价值和专业的建议到项目建设中 Fully involved in different project phase and have valuable input as end user 学习并运用其他工厂和行业的最佳实践到新工厂,如数字孪生、数字化、自动化等前沿技术的引进 Learn and apply best practice from other sites and other experiences to Qingdao project, introduce advanced technical such as digital twin, digitalization, automation to Qingdao site 端到端的精益思维持续标准化和持续改善的理念和能力，通过项目期间的参与，实践为未来的商业化生产的垂直启动和成功做好充足的准备 End to end lean mindset to be involved in project and ensure standardization and continuous improvement to BAU vertical startup through expertise, lean and experience gained from project phase 利益相关方之间良好的内外部沟通 Good communication with stakeholder both internally and externally

生产运营：

Operation

在各种产品组合上开发数据科学解决方案Develop data science solutions on a varied portfolio

设计、创建、测试和实施复杂的模型和算法Design, create, test and implement complex models and algorithms

提供整体分析解决方案，并将其集成到更广泛的用例中

Deliver holistic analytical solutions and integrate them into broader use cases

与PET、供应链、质量、IT和现场数据分析团队建立牢固的关系，以深入了解业务需求。 交付数字化项目，确保按时、足额交付相关数字化用例的流程、人员和资金 Establishing strong relationships with the PET’s, Supply Chain, Quality, IT and above-site Data Analytics teams to develop an in-depth understanding of business needs. Deliver Digital projects ensuring process, people and funding is delivered on time in full for the relevant Digital use cases 规划站点数字用例并确定其优先级： Plan and prioritize site digital use cases 促进站点/PET 进行业务分析，以根据对业务当前状况的了解来识别站点改进的数字机会。 Facilitate Site/PETs for business analysis to identify digital opportunities for site improvements base on understand of current situation of the business. 通过一系列数字用例促进业务、IT 和数据科学家之间的接口，以开发系统改进 Facilitate interface between business, IT and data scientists in developing systematic improvements though a set of digital use cases 详细规划数字用例的优先级，并确保 SLT 批准以执行改进计划 Plan the prioritize the digital uses cases in detail and ensure SLT approval to carry out the improvement program 将非结构化、复杂的业务问题转化为适当的模型和算法解决方案 Translating unstructured, complex business problems into the appropriate model and algorithm solutions 对相关的可用区数据源（包括其质量和结构）有深入的了解 Developing a robust understanding of relevant AZ data sources including their quality and structure 根据需要与供应商合作，以增强分析中的可用区能力 Working with suppliers as needed to augment the AZ capability in analytics 成为 Digital Lighthouse 团队中积极敏捷的成员。 Being an active and agile member of the Digital Lighthouse team. 开发、维护和应用分析和数据科学趋势、最佳实践和新发展方面的持续知识和意识 Developing, maintaining and applying ongoing knowledge and awareness in trends, best practice and new developments in analytics and data science 参与并合作当地数字化论坛，促进知识转移 Participate and partner in local forums for digitalization and promote knowledge transfer 在优先事项和资源承诺上影响当地利益相关者 Influence local stakeholders on priorities & resource commitments 支持PET/职能部门的数字化战略 Support PETs / functions in their digitalization strategy 对潜在的数字化项目进行商业效益分析 Conduct business benefit analysis on potential digital projects 监督围绕数字 LoCo NoCo 解决方案的本地和全球计划 Provide an oversight of local and global initiatives around digital LoCo NoCo solutions

GMP 要求

GMP requirements

理解业务活动中涉及GMP的相关内容及可能对产品质量产生的影响 Understand the impacts of daily work on GMP requirements and product quality 参加GMP相关培训，确保业务活动持续符合GMP要求 Attend GMP trainings and ensure that daily work is compliant to GMP consistently 严格执行本岗位的GMP相关规程 Strictly follow GMP SOPs.

利益相关方

Stakeholder Focus

与工厂内外其他团队建立并保持良好的业务关系 Establishing and keeping good relationship with other teams

Requirements

工程学（计算机科学或电子学）学士学位，或计算机应用、经济学、统计学或数学硕士学位 Bachelor's degree in Engineering (Computer Science or Electronics), or Master’s degree in Computer Applications, Economics, Statistics or Mathematics 5年以上统计和/或数据科学/商业智能工作经验 More than 5 years of working experience in a statistical and/or data science / business intelligence role 熟练掌握 Python、R 或类似编程语言的动手计算机编程 High proficiency in hands-on computer programming in Python, R or similar programming language 有更丰富的大型数据集、模拟/优化和分布式计算工具 High proficiency in exploratory data analysis, data profiling and feature engineering on large, structured and unstructured data sets 有更丰富的大型数据集、模拟/优化和分布式计算工具（Map/Reduce、Hadoop、Hive、Spark 等）经验者优先 Deeper experience of working with large data sets, simulation/ optimization and distributed computing tools (Map/Reduce, Hadoop, Hive, Spark, etc.) is a plus 有图像处理和处理及相关库经验者优先 Experience with image treatment and processing and related libraries is a plus 能够熟练的进行英语读说 Reading and speak English very well 有医药生产或过程管理行业工作经验者优先 Work experience in pharmaceutical production or process management industry is a plus 较强的分析和解决问题的能力Strong analytical and problem-solving skills 对制造和供应链业务领域有很好的理解 Good understanding of manufacturing and supply chain business areas 从容地与多个利益相关者保持开放的合作 Openness to working in agile environments with multiple stakeholders 工业知识 Industrial knowledge

Date Posted

23-5月-2024

Closing Date

30-8月-2024

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