WebHue is a Big Data analytics company that provides measurement and insights into multi-channel retail and marketing. We work with clients like Sears and Microsoft to help them map their business goals to insights and measurable actions. Our DataMesh platform allows clients the ability to integrate large volumes of data, collect data in real-time from ad impression to purchase, and other innovated business intelligent features that we’re cooking up.
As a Data Scientist, you will add a level of data sophistication to WebHue’s products. You will collaborate with a multi-disciplinary team of engineers and analysts on a wide range of problems. This position will bring analytical rigor and statistical methods to the challenges of measuring the impact of social media on purchase behavior, scoring customers to determine their propensity to purchase, attributing revenue correctly to marketing touch points and other business intelligence problems.
• Research, develop, and apply methods for measuring and analyzing large amounts of click-stream and CRM data.
• Develop new algorithms and methods that will be built into WebHue products.
• Research new ways for modeling and predicting end-user behavior.
• Lead investigations into multiple streams of product data.
• Design experiments to answer targeted questions. Conduct exploratory data analysis in high dimensions.
• BA/BS degree in Statistics or other quantitative disciplines such as Engineering, Applied Mathematics, etc. In lieu of degree, 4 years of relevant experience.
• Experience with large data sets using statistical software (R, S-Plus, Matlab, or similar) and large databases (SQL or NoSQL).
• Excellent communication skills, particularly those relating to complex findings and presenting them to ensure audience appeal at various levels of the organization
• MS or PhD in Statistics or other quantitative disciplines such as Engineering, Applied Mathematics, etc.
• Broad work experience with large data sets. Strong experimental design and analysis skills.
• Considerable practical experience in quantitative analysis. Demonstrated leadership and self-direction.
• Ability to draw conclusions from data and recommend actions.
• Willingness to learn new techniques.
• Excellent written and verbal presentation skills.