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About DAT DATis an award-winning employer of choice and a next-generation SaaS technology company that has been at the leading edge of innovation in transportation supply chain logistics for 45 years. We continue to transform the industry year over year, by deploying a suite of software solutions to millions of customers every day - customers who depend on DAT for the most relevant data and most accurate insights to help them make smarter business decisions and run their companies more profitably. We operate the largest marketplace of its kind in North America, with 400 million freights posted in 2022, and a database of $150 billion of annual global shipment market transaction data. Our headquarters are in Denver, CO, with additional offices in Missouri, Oregon, and Bangalore, India. For additional information, see. The Opportunity Developing statistical models utilizing the R and Python coding languages that serve to leverage our Company's comprehensive databases into actionable freight and shipping intelligence and insights for our clients; Developing advanced machine learning models that combine statistical modeling and natural language processing in order to contribute to and continually refine our Company's suite of databases and related analytical offerings; Developing python code libraries, programs, and application which support the analytical and data processes within the team, and across the company, by ingesting and transforming data, testing statistical and machine learning model results, delivering machine learning and statistical model results to databases, applications, and other programming interfaces such as web APIs; Leading and contributing to team problem solving efforts related to data-focused client inquiries and problems, including proactively identifying and fixing issues, and collecting and aggregating client information; Conducting relevant research and data analysis on freight and shipping trends through application of advanced statistical algorithms that run off the R and Python coding languages, as well as Java framework on machine learning platforms such as Apache Spark and H2O; Conducting and delivering quantitative analysis of structured, semi-structured, and unstructured data to both internal and external stakeholders of assigned projects and products; Translating complex data analysis into readable visualizations through the usage of software such as Tableau and Power BI with the goal of delivering clients user-friendly reports that provide them with actionable insights; and Operating within a cross-functional small team in order to develop, test, and harden advanced analytical models, providing statistical and analytical modeling support as needed. In order to complete the above-mentioned tasks, the following skills and experience are required: Strong ability to code in Python, SQL, and R; Experience writing python code as part of a team of engineers and scientists; Experience leading and completing independent research projects in an industry environment; Proficiency in word processing, spreadsheets, and presentation tools, as well as Internet search tools; Strong understanding of machine learning algorithms for classification, regression, and time-series forecasting; Strong understanding of statistics and statistical tests pertaining to evaluation of machine learning models; Ability to coordinate work among multiple teams and stakeholders in the context of programming, machine learning, and mathematical analysis; Ability to clearly present research project design and project results to technical and non-technical colleagues; Experience owning smaller data science products independently, and co-owning important and high-impact products; Experience with Agile methodologies and tools for project management; Experience with cloud computing platforms like AWS, Azure; Experience in data driven analysis using statistical packages in Python or R; and Experience with relation