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# Data Scientist

- **Company:** INNOVATIVE VIDEO TECHNOLOGY, INC.
- **Location:** Ohkay Owingeh, NM, United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** C (Programming Language), Java (Programming Language), JavaScript (Programming Language), A/B Testing, Google AdWords, Amazon S3, Data Analysis, Artificial Neural Networks, Big Data, C++ (Programming Language), Catalyst (Software), Decision Tree Learning, Cluster Analysis, Computer Programming, Databases, Data Architecture, Data Files, Data Mining, Data Presentation, Distributed Data Store, Generalized Linear Model, R (Programming Language), Google Analytics, Apache Hadoop, MapReduce, Apache Hive, Statistical Hypothesis Testing, Python (Programming Language), Machine Learning, MySQL, SQL Databases, Text Mining, Web Services, Facebook Insights, Random Forest, Apache Spark, Deep Learning, Social Network Analysis, Sap Business Objects, Information Technology, Coremetrics (Software), Amazon Redshift, Programming Languages
- **Published:** October 22, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/pthpbd7ccu

## About the Role

Also, the following experience is required to successfully execute the responsibilities assigned to this position:

 * Experience querying databases and using statistical computer languages: R, Python, SQL.
 * Experience using web services: Redshift, S3, Spark, Digital Ocean.
 * Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks.
 * Experience analyzing data from 3rd party providers: Google Analytics, Site Catalyst, Coremetrics, Adwords, Crimson Hexagon, and Facebook Insights.
 * Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, Gurobi, MySQL.
 * Experience visualizing/presenting data for stakeholders using: Periscope, Business Objects, D3, ggplot.
 * Experience using statistical computer languages (R, Python, SQL, etc.) to manipulate data and draw insights from large data sets.
 * Experience working with and creating data architectures.

Other Qualifications:

 * Strong problem-solving skills with an emphasis on product development.
 * Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
 * Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests, and proper usage) and experience with applications.
 * Excellent written and verbal communication skills for coordinating across teams.
 * A drive to learn and master new technologies and techniques.
 * Coding knowledge and experience with several languages: C, C++, Java, and JavaScript.
 * Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, and social network analysis., Candidate must hold a master's degree in computer science, information technology, statistics, informatics, data science, mathematics, or another quantitative field. They must also have 5-7 years of proven work experience as a Data Scientist, specifically in the technology industry., Must be a U.S. citizen and a U.S. Resident

Fully Bilingual (English and Spanish)

## Description

* Work with stakeholders across the organization to identify opportunities to leverage company data to drive business solutions.
 * 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 for data sets.
 * Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting, and other business outcomes.
 * Develop company A/B testing framework and test model quality.
 * Coordinate with different functional teams to implement models and monitor outcomes.
 * Develop processes and tools to monitor and analyze model performance and data accuracy.