Deep Learning APIs


Working with us

Data Scientist/Machine Learning Developer

Metacog measures how learners tackle challenges within assessments, simulations, casual and serious games, and performance tasks. This is a lot more data than simply scores or grades.
We are looking for a Rockstar Data Scientist who can work with our educational data mining experts and development team to help them build engines that surface, analyze, score, and visualize learning pathways and patterns.
If you want to power the next generation of adaptive learning and continuous assessment solutions and provide learners with real-time, dynamic and interactive prescriptive guidance, talk to us. You will be instrumental in developing the next generation learning and assessment technologies that will be key in shaping the future of the U.S. Education System.


· Explore and advise on new data science techniques to take this industry to a new level.
· Develop, design and implement the company's Big Data system using AWS Cloud services.
· Design and implement data models developed by our learning scientists for deeper understanding around learning in interactive digital spaces, including educational games, simulations, and technology enhanced assessment items.
· Build and interpret probabilistic models of complex, highly-dimensional datasets from time series data.
· Write semantic classification algorithms using a combination of Python, Scala, Scalding, R, Julia etc.
· Organize, analyze, retrieve, classify, and report on student json clickstream and log data streams.
· Design and execute software at production scale by utilizing advanced feature generation, machine learning and data mining techniques to estimate learning efficacy and clusters of learning styles.
· Develop and/or assist in the creation of advanced Data visualizations to transform information into insights (like D3.js) These visualizations will be utilized for learning domain experts to identify how to tackle student misconceptions, as well as to discover opportunities to optimize emergent learning pathways.
· Apply advanced data and parallel programming frameworks (Spark or Map/Reduce) to effect real-world solutions. We seek a skilled practitioner who can also advance the state of the art.
· Present to all levels of the organization including peers, senior management, and external customers.

Skills & Requirements

· Experience with supervised and unsupervised machine learning and predictive techniques such as: Bayesian Classification, PCA, Ensembling, Decision Trees, Random Forests, Support Vector Machines, Neural Networks, Clustering and Deep Machine Learning, etc.
· 4+ years experience in analytical and algorithmic design for systems.
· Implementation of Big Data systems such as Hadoop, HBase, Spark, Shark, Storm, Cassandra, Kafka, Apache Drill, MemcacheD, etc. Experience using them in the cloud is a plus.
· Experience with visualization tools and creative data visualization (e.g. heat mapping, radial, and vector-based visualizations) especially for use by non-specialists and educators is a plus.
· Functional data-aware languages (Python, Mathematica or F#) are a strong plus.
· AWS, Big Data, Spark, Scala, Deep Machine Learning.
· 5+ years of application in a broad range of statistical concepts, including predictive and applied statistical modeling. Should have programming experience in Python, R, MPlus, Stata, Matlab, SPSS or other statistical packages.
· Masters (Math, Statistics, CS or physics preferred), Ph.D. or other pertinent industry experience preferred.
· Participation in Kaggle, KDD Cup (or other) competitions a plus.

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