Responsibilities:

• Defines and develops the value proposition for Master Data analytics solutions based on user needs, business value, industry requirements and understanding of advanced analytic models (statistical, operations research, predictive and prescriptive).
• Conceptualizes, builds, develops, and enhances analytic models using right modeling methodology, available structured and unstructured data, cost and timing constraints to solve the large and complex business issues, discovers and delivers compelling and clear business insights across the planning and materials management organization.
• Embeds analytic models into enhanced large scale business processes and operational systems by collaborating with Application Developers.
• Having strong business domain and operations knowledge, to propose strategic solutions and enable predictive insights.
• Drives improvements in PDO metrics such as Engineering Record creation, Order fall-out etc.
• Using unique visualization techniques, condenses large volumes of complex ideas into elegant and simple visual models.
• As a data evangelist, leads weekly meetings with Leaders to provide key insights and align action plans to improve business results.
• Collaborates with stakeholders in various functions of Global Operations to ensure analysis of data considers ongoing business activities including HPE strategies, existing projects, new product introductions, etc.
• Participates in HPE-IT design strategy for resilience and digital transformation.
• Develops agile and scalable models to provide end to end and real time visibility on PDO processes and activities.
• Provides thought leadership on the design of visual management tools and the usage of data science, machine learning, artificial intelligence and other tools to advance supply chain performance.  Collaborates with HPE-IT and EAP functions to address any data quality resolution and data gaps, migrating to platforms etc.

Education and Experience Required:

• Bachelor’s or Master’s degree in IT or Computer Engineering, or equivalent.
• Typically 10-12 years experience in data analytics and overall 15+ years of industry experience
• Masters in Statistics / computer science / operations research / data science / industrial engineering / manufacturing systems
• Deep knowledge in Supply Chain functions and systems knowledge in SAP
• Deep knowledge in Data / business warehousing concepts
• Deep understanding of machine learning/data mining algorithms and techniques
• Experiences in processing and analyzing both structured and unstructured data
• Proven ability to leverage analytical skills and knowledge for business value
• Solid knowledge of big data processing framework in HortonWorks, Clouderc etc and tools, such as Spark, Apache HBase, Hadoop, MapReduce, etc.
• Proficiency in one or more programming languages including but not limited to: Python, Java, Scala, R
• Proficiency in statistical tools such as R, SAS
• Proficiency in visualization tools such as libraries in R, Power BI, QlikSense, Tableau
• Ability to effectively communicate analysis results to customers and negotiate options at management levels
• Excellent analytical and problem solving skills.