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Principal, AI & Machine Learning Engineer 

About the Organization Since 1986 LERETA's nationwide team of real estate tax and flood professionals has provided the mortgage and insurance industries the fastest, most accurate and complete access to property tax and flood information across the nation. With 5.8 million tax loans and over 12 million flood loans under service, LERETA is an industry leader committed to service excellence and providing cost-effective solutions to customers.  
Open Date 11/2/2018  
Position Principal, AI & Machine Learning Engineer  
Full-Time/Part-Time Full-Time  
Exempt/Non-Exempt Exempt  
Category Information Technology  
Location Covina  
Req Number INF-18-00006  

The Principal, AI & Machine Learning Engineer at LERETA will work on machine learning, data mining, and statistical modeling for predictive and prescriptive enterprise solutions. You will be expected to work with a diverse set of data sources, such as time series data, spatial, graph data, semi-structured and unstructured data, and build statistical/machine-learning models in support of on-demand, real-time analytic services

Position Requirements
  • Advanced degree in Computer Science, Engineering, Physics, Mathematics, Statistics
  • 7+ years’ experience in quantitative analysis roles.
  • Experience applying statistics, probability, and machine learning to real business problems.
      • Experience working in the areas of inferential statistics, propensity modeling, machine learning and predictive modeling - experience with packages, such as R, MATLAB, SPSS, SAS, Stata, etc
      • Deep expertise in experiment design, econometrics, causal inference, time-series, econometric forecasting, optimization algorithms, and analytics that support business-critical decision processes
      • Excellent theoretical understanding and hands-on experience with deep learning and a range of more classical supervised and unsupervised machine learning methods, including but not limited to Logistic Regression, Time Series, KMeans, ensemble learning techniques (e.g. boosting, Random Forests) kernel methods (e.g. SVM), (non-linear) dimensionality reduction and feature selection methods are required. Practical knowledge of Bayesian methods and Natural Language Processing
      • Expertise developing algorithms for advanced analytics and experimental measurement, using artificial intelligence, machine learning and statistics for both rapid prototyping and production systems
  • Researching, developing, and implementing predictive algorithms using various regression techniques, deploying them as real-time APIs in our micro-service infrastructure.
  • Utilizing Natural Language Processing to understand text content across products, including reviews and interactions between users, stylists, and products.
  • Research and experiment with different machine learning algorithms and techniques for item classification, product recognition and matching, attribute extraction
  • Strong background working with large-scale data in distributed computing environments, including databases, data cleaning, and feature engineering
EOE Statement We are an Equal Employment/ Affirmative Action Opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, national origin, disability status, protected veteran status or any other characteristic protected by law.  

This position is currently accepting applications.

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