How does government influence finance? What government activities can move financial markets? Which companies benefit from government activities and which are negatively impacted? The Engineering News department is currently working on building new products to help financial professionals answer these questions.
Our team is working on the challenging problem of making sense of a rich set of Government Data from a Financial professional’s perspective. To this end, we intend to apply Machine Learning and NLP techniques for Prediction, Sentiment Analysis, Entity Extraction, Document Clustering and other areas to this vast data set.
We’re looking for an enthusiastic, experienced Machine Learning Software Engineer who can take the initiative and lead Machine Learning efforts within our team. If you enjoy working with Data and like collaborating closely with business stakeholders, specialists and researchers, you’ll fit right in.
We’ll Trust You To
Study disparate Government related data sets
Study current ML and NLP infrastructure and research
Identify ways to gather and build training data
Research models, setup relevant experiments and prototype solutions in Python
Implement and maintain performant, scalable and reliable production systems in C++
Build intuitive and simple user interfaces for busy Financial Professionals


Andiamo Partners (Rec.)


You’ll need to have:
A PhD in NLP, Machine Learning or equivalent experience
3+ years of experience programming in C++, Python or Java
Experience working with SQL
Experience working with Javascript
Strong Computer Science fundamentals (algorithms and data structures)
Strong ability to design solutions to complex problems
We’d love to see:
Experience in user interface design and development
Experience in relational databases
Experience developing in UNIX or Linux
Experience in dynamically typed languages like Python and Lua
Experience in search technologies like Solr, Lucene
Experience working with Hadoop and Spark
Experience working with US Government Data Sets

Educational level:

Ph. D.

Level of experience (years):

Mid Career (2+ years of experience)

Tagged as: , , , , , ,