HP Labs - MemberTechnical Staff - Marketing Science

HP is a leading global provider of products, technologies, solutions and services to consumers and business. The company's offerings span IT infrastructure, personal computing and access devices, global services, and imaging and printing. Our $4 billion annual R&D investment fuels the invention of products, solutions and new technologies so we can better serve customers and enter new markets. We invent, engineer and deliver technology solutions that drive business value, create social value and improve the lives of our customers.

Essential Responsibilities


The Decision Technologies Department (DTD) in Hewlett-Packard Laboratories is seeking to fill the position of Member of Technical Staff.  This person will conduct applied research; build methodologies and tools to address emerging business needs of HP. He/she will be member of a strong team with diverse disciplinary backgrounds including Mathematical Optimization, Stochastic Modeling, Experimental Economics and Game Theory, Data Mining & Machine Learning. The charter of this team is to generate knowledge, and build technologies to help HP’s business processes become more innovative and to spur the growth of HP’s solution & services business. It does so by investigating and developing underlying knowledge for advancing the state-of-the-art in decision support methodologies and by building demonstrative software prototype tools for HP’s businesses and their customers. The applied research work in Business Process Innovation (BPI) portfolio is directed towards manufacturing as well as service supply chains – back-end processes, analytical CRM – customer facing processes and linkages between front-end & back end. 


Some of the current projects in BPI portfolio are: marketing analytics including mix modeling, one-to-one marketing & personalization, marketing campaign management to optimize cross-sell and up-sell opportunities, predictive consumer demand modeling, product proliferation management, modeling of auction processes, demand forecasting & demand shaping, incentive-compatible channel policy design, inventory management, extended supply chain network design, warranty cost management, enterprise risk management, and workforce management.  The goal of the DTD team is to identify and influence business process innovation by jointly working with business units of HP, collaborating with leading researchers in academia, and building methodologies/tools for deployment within HP and also for the needs of HP’s customers through our Services & Solution business unit.


The individual selected for this position should have a good understanding of the current & future trends of analytics methodology based business process innovation areas.  Candidates for this position are expected to have Ph.D. degree in Marketing Science . Applicant should have demonstrated ability to work collaboratively with team members, partners and customers.


 

Skills/Knowledge QualificationsMusts:
Ph.D. in Marketing Science, Quantitative Marketing, or related fields.
In-depth knowledge of many business application areas through graduate course work & research credentials in select few, such as: pricing decisions/revenue management, advertising/promotion decisions, targetability, customer segmentation, consumer choice modeling, competitive analysis, interactions between manufacturers & retailers. This background is demonstrated by scientific publications. 
Strong background in various methodologies through graduate course work & research: optimization, game theory, multivariate analysis, econometric techniques, psychometric approaches & choice models.
Good background in design and development of analytic software.
Experience working with large datasets.
Strong proficiency in statistical software like: R, SAS or Matlab
Pragmatism & an ability to handle ambiguity.
Excellent communication skills.Desired:
Experience in building & successfully deploying innovative mathematical model driven applications in industrial setting.
Graduate level course work in Data Mining/Machine Learning.
Competence in SQL.
Java.
C, C++ programming experience.  Experience in Mathematical Programming software, like Ilog C++ optimization suite of libraries.