- You will be a versatile problem solver, equipped with strong analytical and quantitative skills suited to approach various kinds of challenges in complex environments. Adept at creative and critical thinking, you are able to deconstruct problems and transform personal insights into data backed recommendations. You are a self starter with a strong sense of personal responsibility and a technical orientation. You should have strong coding skills and hands-on Big Data experience You should be proficient in writing code in one of the following languages: C++, R, Java, Python, Perl, in addition to Hadoop experience (MapReduce, Hive, Spark SQL), and R, SQL You will have strong product intuition, data analysis skills and business presentation skills You are capable of working with large sets of data using a variety of tools You have knowledge and experience in implementing and developing customer life cycle predictive models, data structures and interactive tools to improve product You are delivery-oriented, able to lead and execute modeling efforts from start to finish You are expected to lead customer life cycle predictive modeling function, should be self-motivated with a can-do attitude Of course, you are a great teammate with excellent interpersonal skills, and a self starter
Design, develop and manage big data-driven predictive models to solve for product experience and improve user engagement using the latest technologies in machine learning, user pattern recognition, experimentation and data modeling. Analyze data covering a wide range of information from user profile to user behavior signals. Identify new engagement patterns through data mining. Conduct hypothesis driven exploratory analysis, build feature engineering, structure best experimentation design to understand interaction effects of features. Developing test plans, validating engineering & featuring dependencies to launch an experiment, structure experiment design for A/B testing and apply advanced segmentation and statistical models, tools and other capabilities. Collaborate with product, engineering, business, and science groups to formulate innovative solutions to experiment and implement advanced data mining techniques. Work with large volumes of data; extract and manipulate large datasets using tools such as Spark SQL. Communicate complex concepts and the results of the analyses in a clear and effective manner to senior management.
