Job Description :
Role: Machine Learning
Location_ Mason, OH
Position Type: Contract
Preferred
Required Skills/Experience:
Strong Machine Learning experience, some of which is within established technical organizations with production systems.
Deep understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc.
Experience in at least one of these toolkits: Python, R, Weka, SciKit-learn, MATLAB
Familiarity with machine learning frameworks/libraries/packages/APIs (e.g., Theano, Spark MLlib, H2O, TensorFlow, PyTorch, etc
Proven experience in ETL, data processing, transformation, cleaning, and data warehousing techniques
Experience with applied statistics skills, such as distributions, statistical testing, and regression
Experience with widely used probability methods (conditional probability, Bayes rule, likelihood, independence, etc
Experience with time series analysis
Experience with data visualization techniques and tools (e.g., D3JS, ggPlot2)
Good software engineering background (OOP, data structures, algorithms, computability, and complexity)
Excellent conversation and communication skills – able to present on research and tools
Masters in a relevant quantitative field, such as statistics, operations research, or computer science, depending on position level (master''s preferred)
Passionate, Innovative, and Motivated Desired Skills/Experience:
Experience Building Models, and training a deep Neural Net
Experience with Convolutional Neural Networks (CNN)
Proven understanding of multivariable calculus and linear algebra
Experience dealing with massive data sets, using big data tools (Hadoop HDFS, MapReduce, Accumulo, Presto, MongoDB, Cassandra, HBase, R, Mahout, Pig, and Hive, DC/OS)
Hands-on experience and expertise with cloud computing services (AWS, Azure, etc Responsibilities:
Apply data mining and machine learning techniques, perform statistical analysis, and build high-quality prediction systems that solve our customers'' business problems
Explore, interpret, and analyze datasets for patterns of interest
Work closely with various teams to understand our customers’ needs, eventually crafting and pitching machine learning use cases to them
Model business problems to machine learning ones, map business data to dependent and independent features, perform proper feature engineering, iterate with different predictive models, and conduct hyper parameter optimization to yield highest prediction accuracy to deploy the model to production
Keep up to date with latest technology trends in machine and deep learning and quickly learn about new frameworks/techniques to be used in projects delivery.