Principal Data Scientist - eCommerce - PhD

Principal Data Scientist

Define analytic strategies & solutions and the technical requirements of the solutions to meet the demands of business requirements.

- Integrates advanced analytics into end-to-end business intelligence solutions and operational business processes products.

- Conduct sophisticated data mining analyses and build data mining models, as required, to aid in the solution development. Translate data mining results into clear business focused deliverables for decision makers.

- Develop and implement various types of predictive models, machine learning approaches and other data mining solutions creating solutions that help businesses and products make decisions.

- Works with Software/Systems Developers to deploy data mining models into operational systems.

- Designs and/or contributes to the development of a data mining systems that enable reuse, efficiency, manageability and deployment.

- Mentor a deeply technical team of Analytics professionals, Statisticians, Text Mining and Decision Sciences professionals and provide business and technical guidance to them.

- Act as a Principal who analyses and develops enterprise-wide analytics solutions. Leads in the technical assessment and delivery of specific technical capabilities.

- Provides technical oversight to others on solution design, system architecture, tuning and modification of solutions.

- Proactively encourages membership and contributions of others to professional community and coaches others in area of expertise.

- Engages in technical problem solving across multiple technologies; often needs to develop new methods to apply to the situation.

- Regularly produces internally published material such as knowledge briefs, white papers, and design docs to present to peers, team members and stakeholders. Owns and manages knowledge sharing within the internal analytics community.

- Actively collaborate with business analytics, product management, and operations teams and other stakeholders.

Qualifications :

- MS/PhD from a reputed institution. Field of graduate education should be Computer Science, Mathematics, Statistics, Engineering or related fields.

- 10 - 15 years of overall experience in experience in the field of Analytics, Advanced statistics, data mining and preferably working in a product/ecommerce environment.

- Experience with techniques such as Data mining, Advanced Statistics, Pattern Recognition, Machine Learning, Text mining, weblog mining etc.

- Experience in the use of Analytics tools for data mining and statistical analysis in the Supply Chain domain.

Knowledge and Skill Required :

- Expert use of data mining methodologies such as classical regression, logistic regression, CHAID, CART, neural nets, association rules, sequence analysis, cluster analysis, and text mining.

- Expert use of SQL and experience with relational databases.

- Experience with Hadoop, Map/Reduce, Hive or equivalent.

- Excellent communication and presentation skills.

- Has sufficient depth and breadth of technical knowledge to design and scope multiple deliverables across a number of technologies.

- Has demonstrated innovation and communication of new deliverables and offerings.

- Has led team in the delivery of multiple deliverables using multiple technologies.

- Possesses an understanding, at a detailed level, of architectural dependencies of technologies in use in analytics ecosystem.

- Frequently uses product and application knowledge along with internals or architectural knowledge to develop solutions.

- A recognized expert in one or more technologies within own technical community.

- Ability to work in a multi technology environment with the ability to diagnose complex technical problems to their root cause. In addition to troubleshooting skills and consulting skills, has ability to summarize prognosis and impact succinctly.

- Has demonstrated ability to lead others in the gathering of requirements, designs, plans and estimates.

- Demonstrates broad knowledge in other related technical areas in order to properly manage complex integration efforts.

- Passion and deep technical competency in quantitative methods and/or business analytics.

- Strong business focus. Must excel at connecting business requirements to data mining objectives and to measurable business benefit.

- Peer reviewed publications in predictive analytics/statistics/OR/other quantitative areas are a plus.