Entries filed under “Jobs”

Advanti Solutions is seeking a Big Data Engineer in our Job of the Week.

With your strong knowledge of computer science and a deep conceptual understanding of data, youll help Advanti to tackle security identifier issues – one of the most prevalent problems in the equities and fixed income markets. The users of our systems are the quantitative researchers themselves (how awesome?!?) so you will also help us to make their lives easier and empower them do their job better. Well develop data feed adapters into their research content providers and build tight data integration with the statistical computing languages they use, like Matlab, R and SAS.

Are you paying too much for your job ads? Not only do we offer ads for a fraction of what the other guys charge, our insideHPC Job Board is powered by SimplyHIred, the world’s largest job search engine.

Clipped from: inside-bigdata.jobamatic.com (share this clip)

How hot is the Big Data job market? Carolyn Duffy Marsan from Network World writes that Data Scientists are all the rage.

Unheard of 18 months ago, “data scientist” has exploded in popularity as a Google search term. The number of Google searches of “data scientist” hit peaks 20 times higher than normal in the last quarter of 2011 and the first quarter of 2012. It’s a popular search term in high-tech hotspots such as San Francisco, Washington, D.C., and New York. Among the U.S. companies looking to hire data scientists are PayPal, Amazon, and HP. Indeed, the term “data scientist” is mentioned in 195 job listings on the Dice.com website for IT professionals.

Read the Full Story.

Do you you have Big Data jobs to fill? Not only do we offer ads for a fraction of what the other guys charge, our inside-BigData Job Board is powered by SimplyHIred, the world’s largest job search engine.

Paul Sonderegger from Oracle Endeca writes that the biggest bottleneck in making Big Data productive is labor.

In a big data world, data modeling, integration, and performance tuning are governors of data use because they rely on relatively slow manual processes done by relatively expensive specialists. In an ironic twist, the substitution of computing capital for labor that transformed other business processes (such as inventory management, manufacturing, and accounting) will do the same to information management itself. Take the relatively simple case of a data mart with fast-growing volume. As the volume of data grows, query performance tuning becomes both more important and more difficult. Performance tuning requires trade-offs. For example, pre-aggregating the data improves query response but cuts off the user from detailed data which may be valuable for certain investigations. As data volume grows, more data aggregation may be required, eliminating levels of detail that used to be available. When the users rebel, the BI team has to haggle over remediation and strike a new balance. This time-consuming approach is simply unaffordable in a big-data world.

Read the Full Story.