-Knowledgeable about feature engineering and data manipulation
-Python programming (python 2 and 3)
-MongoDB / NoSQL Databases
-SQL / Traditional Databases
-Data manipulation using Python tools
-Familiar with Linux operating system
-Familiarity with collaborative development, including code reviews. Either in a commercial or open source environment
-Strong desire to build efficient and useful tools
-Java / Scala / C++ and associated project management tools (e.g. maven, sbt)
-Data manipulation using Spark or other distributed processing technologies
-Familiar with the Hadoop ecosystem
-Linux shell scripting
-Jenkins or other Continuous Integration platforms
-Worked in a start-up environment
This is an incredible opportunity to work in a company that is the embodiment of a startup culture, with horizontal organizational structure and virtually absent bureaucracy. We value initiative, creativity, and proactive mentality. This is one of the hottest tech niches, where we compete with industry juggernauts, like IBM and SAS, for domination in predictive analytics and machine learning space.
You will be exposed to cutting-edge technologies in this niche, and learn a lot about business applications of machine learning and predictive analytics, with the potential to become a subject matter expert in one of our target niches through acquired knowledge, training and direct access to our programming talent and the product itself.
This position is primarily about implementing very efficient tools and workflows for doing large-scale feature engineering and data manipulation. Having prior experience with data transformation tool development or large scale feature engineering pipelines is a big plus.
Along the way, you will develop comprehensive automated testing to ensure the product is reliable and scalable. You will handle issues and fix bugs promptly to minimize disruption to users as we roll out these state of the art pipelines while also maintaining backwards compatibility. Pairing with and mentoring colleagues is a must. We are a very collaborative team.