Data Mining Engineer - Big Data/HPC (US00006226) Palo Alto, California

Will Develop and implement algorithms for distributed and parallel predictive analytics while staying up-to-date w/research & innovative 3rd party products addressing storage & analysis of large datasets from real-world problems. While working with a highly skilled team and stakeholders in the US and overseas, will develop distributed/parallel solutions for predictive analytics and visualization of structured & unstructured data sets, and design test cases to evaluate run-time & predictive performance of parallel/distributed algorithms, while improve scalability / performance of existing storage and analytics solutions.

·    Practical exp. in developing algorithms & appl. using MapReduce, MPI, or similar frameworks.
·    Exp. parallelizing algorithms in MPI, MapReduce, OpenMP, or similar parallel environment.
·    Exp. w/distributed file systems & working knowledge of NoSQL or other distributed DTB systems.
·    Demonstrated exp. w/relational database systems and familiarity with SQL.
·    Proven expertise in applying descriptive and inferential statistics in Big Data.
·    Competence in theory & application of standard machine learning or data mining algorithms.
·    Need Linux OS system internals, storage concepts, & networking topologies & protocols.
·    Exp. identifying performance bottlenecks w/network, I/O, OS, DBMS configuration.
·    Experience with 2 or more of the following: Java, C++ (STL), Python, Perl, MATLAB, R, SPSS, SAS.
·    Experience with HBase, Hive, Pig, Cassandra, or similar technologies - Mahout (a plus)

The Client's Research and Technology Center North America (RTC), with an office in Palo Alto, CA, focuses on the topics of sensor and communication technologies, including MEMS integration techniques and RF applications; new powertrain concepts; communication systems for automotive and industrial applications; and human-machine-interaction and visualization technologies. By choice, we are an Equal Opportunity Employer committed to a diverse workforce.

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