We are building the predictive analytics platform to make the world more productive, reliable, safe and secure. We take data from an expanding range of industries and combine our strengths in data science and software development to deliver actionable insights to companies worldwide. This creates quantifiable efficiencies for businesses, and dynamic challenges for us.
What you'll do:
Collaborate with a team to analyze problems
Write functions/scripts to build datasets base
Model building and testing
Writing informal reports for internal use
Working with developers and implementation engineers to spec out database models and determine implementation of algorithms
With slightly less frequency, the individual may:
Meet with a client to understand the needs for a project
Write a project scope for a consultant, as well as potentially managing the consulting relationship
Knowledge of R, Matlab, or Python
Knowledge of building time series, spatial, or financial forecasting models for prediction
Familiarity with any or all of the following:
Dirichlet Latent Process
Time series analysis (GARCH, auto-regressive or moving average, etc.)
Random forest and decision tree models
Bachelor's Degree in Computer Science, Operations Research, Statistics, or related field.
Requires travel up to 20% of the time.
Must also have authority to work permanently in the U.S.
Knowledge of one or more of C++, C, Java, Scala
Previous published academic research in artificial intelligence, machine learning, or operations research
Open source contributions in areas such as machine learning, distributed systems, and databases
Top 5% finishes in Kaggle competitions
Why Work Here
We build and deliver, then explore to build more. Curiosity and flexibility enable everything we do, and we get stronger as we make each new industry smarter. As a team, we bring our diverse backgrounds, beliefs and experiences to solve problems no one has yet to solve, at a speed no one has yet to experience. We support and challenge one another to bring out a new best in each of us, and we might have a little fun along the way.