Data ScientistThe Data Scientist is responsible for supporting data science initiatives that drive business profitability, increased efficiencies, and improved customer experience. This role applies industry-leading analytical methodologies for working with large datasets to extract meaningful business insight and creatively solve business problems. Data Scientists are also responsible for ensuring that developed codes are documented into a library of reusable algorithms. Based on the specific data science team, this role would need to be knowledgeable in one or more data science specializations, such as optimization, computer vision, recommendation, search, or NLP. As a Data Scientist, you will apply advanced analytics methods and algorithms for identifying trends and providing business solutions. This role is expected to present insights and recommendations to non-technical audiences and explain the benefits and impacts of the recommended solutions. In addition, Data Scientists collaborate with business partners and cross-functional teams, requiring effective communication skills, building relationships, and focus on understanding the overall business area being supported.

Key responsibilities include

Solution Development

• Design and develop algorithms and models to use against large datasets to create business insights; Participates in large data analytics project teams by serving as a technical lead for analytics projects; May lead small projects and work independently on solution development; Execute tasks with high levels of efficiency and quality; Make appropriate selection, utilization, and interpretation of advanced analytical methodologies

Communicating Results

• Effectively communicate insights and recommendations to both technical and non-technical leaders and business customers/partners; Present recommendations in a confident manner in order to influence execution of recommendation; Prepare reports, updates, and/or presentations related to progress made on a project or solution; Clearly communicate impacts of recommendations to drive alignment and appropriate implementation

Business Collaboration

• Incorporate business knowledge into solution approach; Effectively develop trust and collaboration with internal customers and cross-functional teams; Work with project teams and business partners to determine project goals

Technical Exploration & Development

• Seek further knowledge on key developments within data science, technical skill sets, and additional data sources; Participate in the continuous improvement of data science and analytics by developing replicable solutions (for example, codified data products, project documentation, process flowcharts) to ensure solutions are leveraged for future projects; Build and maintain library of reusable algorithms for future use, ensuring developed codes are documented

This position typically reports to Manager or above and has 0 Direct Reports. Typically requires overnight travel less than 10% of the time. Most of the time is spent sitting in a comfortable position and there is frequent opportunity to move about. On rare occasions there may be a need to move or lift light articles. Located in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable.

Minimum qualifications include being eighteen years of age or older and legally permitted to work in the United States.

Preferred qualifications include a Masters or PhD in a quantitative field (Computer Science, Math, Statistics, etc.) or equivalent work experience, 3

years of work experience in developing machine learning/AI models to solve business problems, 3

• years of experience in business intelligence and analytics, proficiency in a modern scripting language (preferably Python), proficiency running queries against data (preferably with Google BigQuery or SQL), knowledge in Prescriptive Modeling like optimization, computer vision, recommendation, search, or NLP, demonstrated experience in predictive modeling, data mining, and data analysis, proficiency with data visualization software (preferably Tableau), proficiency utilizing statistical techniques to identify key insights that help solve business problems, and working knowledge of Microsoft Excel and Power Point.