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Data Scientist

SaveSoft, Inc
Los Angeles, California, United States
April 10, 2019


Jr. Data Scientist

Job Summary:

This role is responsible for the development and execution of new machine learning predictive modeling algorithms, the coding\development of tools that use machine learning/predictive modeling to make business decisions, searching for and integrating new data (both internal and external) that improves our modeling and machine learning results (and ultimately our decisions), and discovery of solutions to business problems that can be solved through the use of machine learning/predictive modeling. This role will also begin to manage projects of small to medium complexity.

Key Responsibilities:

• Uses best practices, with limited coaching, to develop statistical, machine learning techniques to build models that address business needs

• Utilizes effective project planning techniques to break down basic and occasionally moderately complex projects into tasks and ensure deadlines are kept

• Uses and learns a wide variety of tools and languages to achieve results (e.g., R, SAS, Hadoop)

• Collaborates with the team in order to improve the effectiveness of business decisions through the use of data and machine learning/predictive modeling

• Innovates on projects by using new modeling techniques or tools

• Contributes on a wide variety of projects

• Executes on modeling/machine learning projects effectively

• Communicates findings to team and leadership ensure models are well understood and incorporated into business processes

• Works with leaders to ensure the project will meet their needs

• Maximizes personal professional development to ensure continuation of a personal contribution to the team and Allstate

• Reviews and evaluates on appropriateness of techniques, given current modeling practices, to senior leadership

Job Qualifications:

• Degree in a quantitative field such as statistics, mathematics, computer science, finance.

• Experience in using statistical modeling and/or machine learning techniques to build models that have driven company decision making preferred

• Experience in managing and manipulating large, complex datasets

• Experience in working with statistical software such as SAS, R, etc. preferred

• Demonstrated Analytic Agility

• Ability to analyze and interpret moderate to complex concepts

• Ability to provide written and oral interpretation of highly specialized terms and data, and ability to present this data to others with different levels of expertise