Dell provides the technology that transforms the way we all work and live. But we are more than a technology company — we are a people company. We inspire, challenge and respect every one of our over 100,000 employees. We also provide them with unparalleled growth and development opportunities. We can’t wait for you to discover this for yourself as a Senior Advisor Data Scientist on our Data Science team in Beer Sheva and Hertzlia sites.
Dell is committed to the development of data-driven and high business value machine learning and artificial intelligence use cases and solutions. We are looking for talented individuals to join our data science team, which is developing a fundamentally new approach to how business generates meaning from data.
Our team develops new methodologies, capabilities and tools to enable advanced modeling and statistical analysis of business data and very often, very large business data. Our Data science team works with prospects and internal customers to prove the analytical capabilities of Dell’s technology in generating business insights from big data.
A member of our Data Science team is charged with understanding and prioritizing our business and customers’ most urgent data driven problems and opportunities, and use advanced mathematical methods and models to provide answers.
Our Data Scientists develop new practices and methodologies for working with the Dell data warehouse technology, working closely with leading academics and industry experts – often as part of pilot projects. Team members also work with engineers to create new tools and features that support sophisticated machine learning and data science capabilities.
Key responsibilities
Work, under little to no supervision on tight schedule projects, with internal and external teams to understand customer requirements and develop proposals and data-driven, AI solutions to address to those requirements
Lead and perform end-to-end steps involved in solution development, while establishing subject-matter expertise in key horizontal or vertical themes. Steps include preliminary data exploration and data preparation steps, variable/algorithm selection, model development/validation and scoring. Horizontal themes include: Marketing Analytics, Operations Research, Text Analytics, Graph Analytics, Hadoop, etc. Vertical themes include: Financial Services, Retail/CPG, Energy, Life Sciences, etc.
Independently develop and drive the model development lifecycle, testing of algorithms' efficacy (i.e., by applying to test/sampled data and assessing accuracy/fit/predictivestrength) for differing analytical use-cases
Develop and apply a broad range of techniques and theories from statistics, machine learning, and business intelligence to deliver actionable business insights to prospects and customers based on large-scale data
Communicate and explain results and insights to business executives throughout projects’ life cycle
Lead the definition of project use-cases, scope definition, and ongoing interaction with customers and business partners to provide status updates and shares analytical insights
Collaborate with internal sales teams to educate prospects and customers on analytics offerings while leading pre-sales discussions by presenting on analytics service offering and technology stack
Generate new product requirements for the engineering group to enhance the analytics capabilities of the big data platform, in alignment with emerging subject-matter expertise
Serve as spokesperson on specialized projects and act as prime consultant on large projects and may be an informal team leader
Contribute to partnerships & relationships with third parties by developing/testing vertical/horizontal analytical solutions and product integrations
