דרושים ב-Ge Healthcare ב-Poland, Krakow

Responsibilities

• Insights Strategy Development: Develop and implement comprehensive insights strategies to support business goals and drive data-driven decision-making

• Data Analysis: Analyze large and complex data sets to uncover trends, patterns, and insights that inform business strategies

• Cross-Functional Collaboration: Work closely with various departments, including finance, services, supply chain, marketing, sales, and product development, to ensure insights are integrated into decision-making processes

• Reporting and Visualization: Create clear and compelling reports and visualizations to communicate insights to stakeholders at all levels of the organization

• Stakeholder Engagement: Engage with senior leadership and other key stakeholders to present findings and recommendations

• Continuous Improvement: Identify opportunities for process improvements and implement best practices in data analysis and insights generation

• Leverage expertise in insights and analytics, as well as the latest industry knowledge to accelerate the innovation of data-driven insight solutions

• Evaluate information from various sources to provide insights and strategic direction.

Required Qualifications & Skills

• A Bachelor’s degree (preferably in a science, data, engineering, or a business discipline); an MBA or Master’s degree preferred,

• Advanced data and analytics experience, including an emphasis on strategic analytics and insights,

• Previous experience managing complex projects and portfolios to deliver business outcomes,

• Proven success communicating and engaging with executives; ability to communicate, influence, and engage partners, stakeholders and influencers across organizational levels,

• Proven experience in data analytics, preferably within the finance sector,

• Strong analytical and problem-solving skills with the ability to interpret complex data and provide actionable insights,

• Proficiency in data analysis tools (e.g., SQL, Python, R) and data visualization tools (e.g. Power BI),

• Knowledge of advanced analytics techniques and machine learning,

• Experience with cloud-based data platforms (e.g., AWS, Azure),

• Ability to develop and deliver creative solutions that best meet stakeholder and business needs,

• Expertise in applying data analysis, data science, forecasting, decision analytics, BI reporting and other analytics frameworks and techniques to influence business decisions,

• Strong communication, presentation and facilitation skills.

Strategic Leadership:

• Developing and executing a data architecture strategy aligned with the company's business objectives and data analytics roadmap.

• Defining and maintaining the enterprise data model, data standards, and data governance policies.

• Staying abreast of emerging technologies and trends in data architecture, data integration, and data governance, evaluating their potential impact on the data architecture.

Technical Leadership & Architecture:

• Leading the design and implementation of data integration patterns, data pipelines, and data solutions on AWS.

• Overseeing the evolution of our data lake, data warehouse, and related data services, ensuring scalability, reliability, and security.

• Providing architectural guidance and oversight for data-related projects across the organization.

• Analyzing, designing, and developing a solution roadmap and implementation plan based upon a current vs. future state of the business.

• Participating in the Enterprise Architecture domain governance model.

• Contributing to the development of software, data and technology platforms with reusable components that can be orchestrated together into different methods.

• Leading the research and evaluation of emerging technology, industry and market trends to assist in project development and/or operational support actives.

Team Leadership & Development:

• Leading, mentoring and develop a team of Data Architects, providing technical guidance, performance feedback, and career development opportunities.

• Fostering a collaborative and innovative team environment.

• Promoting knowledge sharing and best practices within the team and across the broader Data Analytics organization.

• Managing budgets and strategic inputs into short/long term budget planning.

Collaboration & Stakeholder Management:

• Partnering closely with Data Scientists, Data Engineers, Business Analysts, and other stakeholders to understand their data needs and deliver effective solutions.

• Collaborating with Enterprise IT to ensure alignment with overall IT strategy and governance.

• Communicating technical concepts and solutions effectively to both technical and non-technical audiences.

Required Qualifications

• Bachelor's degree in Computer Science, Engineering, or a related field. Master's degree preferred.

• Strong experience in data architecture, data modeling, or related roles.

• Experience in leading and managing technical teams.

• Deep expertise in cloud computing, specifically AWS (Amazon Web Services). Experience with services such as S3, EC2, EMR, Glue, Athena, Redshift, Kinesis, Lambda, and IAM is essential.

• Proven experience in designing and implementing data lakes, data mesh, data warehouses, and data pipelines.

• Strong understanding of data modeling techniques (relational, dimensional, NoSQL).

• Experience with data integration tools and techniques (ETL/ELT).

• Technical Expertise: AWS Cloud Services, Data Modeling, Data Warehousing, Data Lake Architecture, ETL/ELT Processes, Data Governance, Data Security, Metadata Management, Data Lineage.

• Leadership: Team Management, Mentoring, Strategic Thinking, Communication (written and verbal), Problem-Solving.

• Soft Skills: Collaboration, Influence, Adaptability, Results-Oriented.

Core Responsibilities

• Develop and implement advanced AI algorithms and models to solve complex problems across finance, manufacturing, quality, supply chain, sales & marketing.

• Develop and implement advanced forecasting methodologies using technologies like batch forecasting, deep learning, simulation, and reinforcement learning to enhance decision-making.

• Apply computer vision methods to drive manufacturing efficiencies and improve product quality across the GE Healthcare manufacturing network.

• Collaborate with cross-functional teams to integrate AI solutions into various applications and products.

• Analyze large datasets to extract meaningful insights and improve model performance.

• Design and conduct digital experiments to validate and optimize AI models.

• Present findings and recommendations to stakeholders in a clear and concise manner.

• Collaborate with the MLOps team during AI model development, deployment and monitoring.

• Proactively identify new opportunities to further leverage data science solutions – prioritizing opportunities with the biggest potential benefit to the business.

• Ensure best practice adoption within the Enterprise AI team, applying appropriate levels of technical capability, standardization, and subject matter expertise.

• Drive a culture of analytics and fact-based decision making through the utilization of standard methodologies and approaches.

Experience Requirements

• M.S. or Ph.D. in Computer Science, Data Science, Engineering or a STEM related field with hands-on experience in developing and deploying AI models and applications.

• Proficiency in the latest Python, AWS, Azure, and open-source data science tools such as Jupyter, R, SQL, Hadoop, Spark, TensorFlow, Keras, PyTorch, and Scikit-learn.

• Proficiency in AI agentic development tools such as AWS Bedrock, Azure AI Foundry, Microsoft Copliot Studio and LangChain/LangGraph.

• Knowledge of RAG architecture, including retrieval mechanisms and generative models.

• Knowledge of deep learning architectures including CNNs, RNNs, and GANs.

• Experience building RAG models and AI agents via AWS or Azure AI services.

• Ability to work with large-scale datasets and perform efficient data analysis.

• Expertise in transformers, self-supervised learning, and generative AI models.

• Strong problem-solving skills and the ability to think critically and creatively.

• Excellent communication skills and the ability to work collaboratively in a team environment.

Responsibilities

• Insights Strategy Development: Develop and implement comprehensive insights strategies to support business goals and drive data-driven decision-making

• Data Analysis: Analyze large and complex data sets to uncover trends, patterns, and insights that inform business strategies

• Cross-Functional Collaboration : Work closely with various departments, including finance, services, supply chain, marketing, sales, and product development, to ensure insights are integrated into decision-making processes

• Reporting and Visualization: Create clear and compelling reports and visualizations to communicate insights to stakeholders at all levels of the organization

• Stakeholder Engagement: Engage with senior leadership and other key stakeholders to present findings and recommendations

• Continuous Improvement: I dentify opportunities for process improvements and implement best practices in data analysis and insights generation

• Leverage expertise in insights and analytics, as well as the latest industry knowledge to accelerate the innovation of data-driven insight solutions

• Evaluate information from various sources to provide insights and strategic direction.

Required Qualifications & Skills

• A Bachelor’s degree (preferably in a science, data, engineering, or a business discipline); an MBA or Master’s degree preferred,

• Advanced data and analytics experience, including an emphasis on strategic analytics and insights,

• Previous experience managing complex projects and portfolios to deliver business outcomes,

• Proven success communicating and engaging with executives; ability to communicate, influence, and engage partners, stakeholders and influencers across organizational levels,

• Proven experience in data analytics, preferably within the finance sector,

• Strong analytical and problem-solving skills with the ability to interpret complex data and provide actionable insights,

• Proficiency in data analysis tools (e.g., SQL, Python, R) and data visualization tools (e.g. Power BI),

• Knowledge of advanced analytics techniques and machine learning,

• Experience with cloud-based data platforms (e.g., AWS, Azure),

• Ability to develop and deliver creative solutions that best meet stakeholder and business needs,

• Expertise in applying data analysis, data science, forecasting, decision analytics, BI reporting and other analytics frameworks and techniques to influence business decisions,

• Strong communication, presentation and facilitation skills.

Responsibilities:

• Act as consultant and subject matter expert for various development initiatives in SAP WM and SAP MM area maintaining digital technology and functional peer relationships across the organization.

• Ensure smooth transition for SAP Warehouse and Material Management into SAP S/4 Hana.

• Deliver innovative solutions leveraging related technologies to meet requirements arising from programs, evolving regulatory environment and business development initiatives.

• Support ongoing business operations resolving incidents and realizing continuous improvement opportunities. Contribute to on-going SAP system vitality programs.

• At all times adhere to GxP and IT QMS standards and deliver highest quality process design, functional requirements, configuration, testing and documentation.

• Work closely with relevant business functions across all PDx global sites to maintain a detailed and current knowledge of their organization, processes, priorities and system needs.

• Assist SAP DevOps leadership team in planning by providing resource and development estimates related to upgrades, projects, and new implementations

Requirements:

• Expertise in Warehouse/Material Management/Logistics area in SAP ECC or SAP S/4 Hana EWM

• Proficiency in using and customizing SAP WM/EWM/MM features and functionalities

• Business process analysis, business process design, requirements management, functional design, and implementation experience.

• Knowledge of integrations leveraging different interfacing technologies/tools especially related to integrations with 3rdParty Warehouses.

• Knowledge of key SAP warehousing functionality including Handling Unit Management, RF Mobile Device functionality.

• Analytical skills and ability to form effective solutions.

• A relevant degree from University/College.

• Excellent spoken and written English skills.

Education and Experience:

• Bachelor’s Degree in Computer Science, “STEM” Majors (Science, Technology, Engineering and Math) or Business Management – or equivalent relevant qualification/experience

• Experience with Application Development, Application Maintenance and support preferably within SAP Applications.

Responsibilities

• Develop and implement advanced AI algorithms and models to solve complex problems across finance, manufacturing, quality, supply chain, sales & marketing.

• Develop and implement advanced forecasting methodologies using technologies like batch forecasting, deep learning, simulation, and reinforcement learning to enhance decision-making.

• Apply computer vision methods to drive manufacturing efficiencies and improve product quality across the GE Healthcare manufacturing network.

• Collaborate with cross-functional teams to integrate AI solutions into various applications and products.

• Analyze large datasets to extract meaningful insights and improve model performance.

• Design and conduct digital experiments to validate and optimize AI models.

• Present findings and recommendations to stakeholders in a clear and concise manner.

• Collaborate with the MLOps team during AI model development, deployment and monitoring.

• Proactively identify new opportunities to further leverage data science solutions – prioritizing opportunities with the biggest potential benefit to the business.

• Ensure best practice adoption within the Enterprise AI team, applying appropriate levels of technical capability, standardization, and subject matter expertise.

• Drive a culture of analytics and fact-based decision making through the utilization of standard methodologies and approaches.

Experience Requirements

• B.S. in Computer Science, Data Science, Engineering or a STEM related field with basic hands-on experience in developing and deploying AI models and applications.

• Proficiency in the latest Python, AWS, Azure, and open-source data science tools such as Jupyter, R, SQL, Hadoop, Spark, TensorFlow, Keras, PyTorch, and Scikit-learn.

• Proficiency in AI agentic development tools such as AWS Bedrock, Azure AI Foundry, Microsoft Copliot Studio and LangChain/LangGraph.

• Knowledge of RAG architecture, including retrieval mechanisms and generative models.

• Knowledge of deep learning architectures including CNNs, RNNs, and GANs.

• Experience building RAG models and AI agents via AWS or Azure AI services.

• Ability to work with large-scale datasets and perform efficient data analysis.

• Expertise in transformers, self-supervised learning, and generative AI models.

• Strong problem-solving skills and the ability to think critically and creatively.

• Excellent communication skills and the ability to work collaboratively in a team environment.

Responsibilities

• Insights Strategy Development : Develop and implement comprehensive insights strategies to support business goals and drive data-driven decision-making

• Data Analysis: Analyze large and complex data sets to uncover trends, patterns, and insights that inform business strategies

• Cross-Functional Collaboration: Work closely with various departments, including finance, services, supply chain, marketing, sales, and product development, to ensure insights are integrated into decision-making processes

• Reporting and Visualization : Create clear and compelling reports and visualizations to communicate insights to stakeholders at all levels of the organization

• Stakeholder Engagement: Engage with senior leadership and other key stakeholders to present findings and recommendations

• Continuous Improvemen t: Identify opportunities for process improvements and implement best practices in data analysis and insights generation

• Leverage expertise in insights and analytics, as well as the latest industry knowledge to accelerate the innovation of data-driven insight solutions

• Evaluate information from various sources to provide insights and strategic direction.

Required Qualifications & Skills

• A Bachelor’s degree (preferably in a science, data, engineering, or a business discipline); an MBA or Master’s degree preferred,

• Advanced data and analytics experience, including an emphasis on strategic analytics and insights,

• Previous experience managing complex projects and portfolios to deliver business outcomes,

• Proven success communicating and engaging with executives; ability to communicate, influence, and engage partners, stakeholders and influencers across organizational levels,

• Proven experience in data analytics, preferably within the finance sector,

• Strong analytical and problem-solving skills with the ability to interpret complex data and provide actionable insights,

• Proficiency in data analysis tools (e.g., SQL, Python, R) and data visualization tools (e.g. Power BI),

• Knowledge of advanced analytics techniques and machine learning,

• Experience with cloud-based data platforms (e.g., AWS, Azure),

• Ability to develop and deliver creative solutions that best meet stakeholder and business needs,

• Expertise in applying data analysis, data science, forecasting, decision analytics, BI reporting and other analytics frameworks and techniques to influence business decisions,

• Strong communication, presentation and facilitation skills.