Data Scientist – Statistics, Hewlett-Packard Enterprise, Palo Alto, CA

Candidates for this position are expected to have a Ph.D. degree. The person will be responsible for building state-of-the-art advanced analytics models while utilizing massive structured and unstructured information for several applied areas, including customer segmentation, attribution modeling, marketing campaign design, product recommendations, personalization, predictive analytics modeling to capture customer requirements. This position offers a unique opportunity to make strong impact in demand generation of HPE’s products/services by mining customer information while optimizing the costs. This is an opportunity for the right candidate to be part of a strong interdisciplinary analytics core team with strong skills in large scale optimization, statistics, computer science, and marketing science. This team maintains strong research partnership in select areas with leading researchers in academia. In 2009, this team was responsible for product portfolio management technology development and deployment, which resulted in HP winning the INFORMS Edelman Award. In 2012, this team won the INFORMS Revenue Management and Pricing Section Practice Award for outstanding applications of revenue management and pricing methodologies.

The candidate should have a keen interest in innovative applied development to drive high business impact. Applicant should be interested in and committed to solving real business problems and should have demonstrated ability to work collaboratively with team members across geographical boundaries, with partners in various business units, with customers and academic partners. He/she should possess strong algorithmic software development skills.

Candidate must have received a Ph.D. degree in last 0-3 years.

Skills/Knowledge Qualifications

Musts:

• PhD in Statistics, Marketing Science or Econometrics.
• The candidate should be familiar and experienced with advanced statistical methods, including but not limited to: Bayesian statistical methods, time series analysis, high-dimensional inference, statistical learning, and semiparametric regression. Strong background and skills in empirical work.
• Graduate level course work in data mining and machine learning.
• Experiences with commercial and open source statistics packages (like R, SAS) & data mining softwares.
• Excellent background in design and development of complex algorithmic software prototypes.
• Work effectively in a cross-disciplinary research team with a focus on developing novel statistical methods motivated by large-scale real world business problems.
• Communicate effectively with statisticians & non-statisticians.

Desired:

• Strong familiarity & experience with select data mining methods and techniques, like feature selection, classification and text mining.
• Excellent programming skills in one or more: R, SAS, Java, C, C++, C#, VBA, SQL, Python
• Experiences in handling and preparing large real-world datasets
• Graduate level course sequence in Econometrics and/or Marketing Science.
• Graduate level course work in mathematical optimization.