South BayGeo Meetup Message Board › Got Brains?
|A former member||
Web Analytics, Statistics
Located in Redwood City
Sr. Analytic Scientist / Engineer
My client is the leading provider of personalized product recommendations for online retailers. The company builds deep profiles based on each individual shopper's behavior, and then uses a patented portfolio of algorithms and real-time optimization to deliver the most relevant recommendations. My clients' clients are increasing average order value by 45 percent, improving conversion rates by 90 percent, and boosting overall online revenue 10-30%. Premier retailers -- including Lancôme, Wine Enthusiast and Cost Plus World Market -- partner with my client to offer intelligent, personalized recommendations to their shoppers. Based in Redwood City, CA
This is a senior position who will be a key member of our Analytics team in the Engineering organization responsible for developing the company's advanced technology in predictive modeling and large-scale data analytics. Your solutions will drive the effectiveness of my clients Recommendation engine, enabling it to find the most relevant product recommendations for each consumer based on that consumer’s unique profile.
Key areas of responsibility include:
Design and develop new analytic components for my clients product recommendation service and learning engine
Use your experience in machine learning, behavioral analysis, and data mining to provide practical and scalable solutions for contextual, behavioral and demographic personalization and text analysis
Develop prototypes using industry standard tools (Weka, R, MatLab) to predict effectiveness of recommendations, and then implement scalable, reliable, automated production quality solutions on in Java on Linux/Oracle tech stack
Design and develop methods of tracking the experiments and operational statistics that measure the performance and effectiveness of my client’s service
Day to day tasks will range from data management & exploration to engine performance modeling/tuning to creative identification and estimation of preference-models and classification-schemes
Use data mining and analytics on a variety of retailer product data and consumer profile information (browsing behavior, preferences) to maximize response rate
Analyze and report model performance and optimization results
This position will challenge you not only to handle large data sets with ease, but also to develop sophisticated statistically-based predictive systems built around this data. You will be expected to be self-guided and to be genuinely curious about what makes things tick.
PhD or MS in Statistics, Applied Statistics, Computer Science, or Applied Mathematics.
10+ years industry experience providing mathematical solutions to business issues, preferably related to online product recommendations, web based personalization, behavioral ad networks, behavioral eMarketing
Practical industry experience using multiple analytical methodologies including Bayesian methods, Neural Networks, Collaborative Filtering, and Cluster Analysis
4+ years experience developing high performance solutions in Java on Linux/Oracle
Working experience with large data sets on Oracle 10g, SQL, PL/SQL
Deep knowledge of relevant metrics for real-time systems
Excellent understanding of data mining techniques on large sets of consumer behavioral and product data.
Experience with Testing and Optimization desirable
Ability to communicate technical ideas effectively, in oral and written forms, and solve complex problems in team environment.
High commitment to excellence, collaboration and team achievement
Experience using statistical/mathematical tools such as Weka, SAS, R, Matlab to assist in data analytics and modeling