Data Science Engineer

Better Engineers. Better Results. SalsaMobi connects accomplished Software Engineers across the Americas with our portfolio of high-growth and newsworthy technology companies in the United States. Senior Engineers in the SalsaMobi network work remotely with some of the most interesting tech companies in the world. Join us today and experience a life where talent has no borders.

We are looking for a Sr Data Scientist who will support multidisciplinary teams with data insights. The ideal candidate is adept at using large data sets to find opportunities for product and process optimization. They must have strong experience using a variety of data mining and data analysis methods, using a variety of data tools, building and implementing models, and using and creating algorithms. They are also well-versed in US consumer behavior trends and ways to reach those consumers online and in social media. They must have a proven ability to drive business results with their data-based insights.  

Responsibilities: 

• Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques, and business strategies.
• Assess the effectiveness and accuracy of new data sources and data gathering techniques.
• Develop custom data models and algorithms to apply to data sets.
• Use predictive modeling based on consumer behavior, to increase and optimize customer experiences, revenue generation, ad targeting, and other business outcomes.
• Data mining using state-of-the-art methods
• Develop company A/B testing framework and test model quality.
• Develop processes and tools to monitor and analyze model performance and data accuracy.

Requirements:

• Degree in Computer Science, Statistics, Applied Math or related field
• Good applied statistics skills, such as distributions, statistical testing, regression, etc.
• 5+ years’ practical experience with SAS, ETL, data processing, database programming, and data analytics
• Extensive background in data mining and statistical analysis
• Able to understand various data structures and common methods in data transformation
• Excellent pattern recognition and predictive modeling skills
• Experience with programming languages such as Java/Python an asset
• Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc.

Nice to Have: 

• Knowledge and experience in Random Forest, Boosting, Trees, text mining, social network analysis, etc.
• A drive to learn and master new technologies and techniques.
• Experience with common data science toolkits, such as R, Weka, NumPy, MatLab, etc
• Experience with data visualisation tools, such as D3.js, GGplot, etc.

All your information will be kept confidential according to EEO guidelines.

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