Marketing Data Science Fellow

Description

Acts independently on behalf of the department to provides dynamic leadership at the enterprise level related to vast quantities of data, enterprise analytics, statistical modeling, and artificial intelligence (Al)/machine learning (ML) initiatives. Uses expert knowledge of data on customers, consumers, economy, external demand drivers, market, and competition (structured and unstructured) and internal business processes to develop advanced analytical solutions to ambiguous and very highly complex business problems. Breaks down ambiguous problems into manageable data science tasks, creating and executing data-driven solutions, and communicating results effectively to a diverse audience. Provides thought leadership, leading cross-functional teams, and making expert use of current and emerging technologies to derive actionable insights and recommendations for business partners and management. Breaks down highly ambiguous and complex problems into well-defined data science/analytics tasks that can be solved with data and modeling/analytical approaches. Creates and executes solutions from initial concept to fully tested production and communicates results to a broad range of audiences. Provides thought leadership and leads cross-functional and crosscompany teams in the more advanced descriptive, diagnostic, predictive and prescriptive modeling, advanced statistical analysis, and other quantitative analysis of complex business situations. Makes expert use of current and emerging technologies to evaluate trends and develop actionable insights and recommendations to business partners and management. Makes expert use of data, statistical and quantitative analysis, explanatory and high-complexity predictive modeling, and fact- based management to drive decision-making. Leads cross functional projects and programs, formally preparing and presenting to senior management. Provides expert consultation to senior management on a regular basis. Routinely works on multiple highly complex assignments concurrently. Mentors less senior staff. Perform other duties as assigned. Master’s degree in data science, analytics, business, mathematics, economics, computer science or other quantitative fields such as engineering/operations research plus 4 years of experience in the job offered or 4 years of work experience in data science, analytics, business, mathematics, economics, computer science, or other quantitative fields such as engineering/operations research, in an analytical, quantitative, or technical role. The employer will alternatively accept a PhD in data science, analytics, business, mathematics, economics, computer science or other quantitative fields such as engineering/operations research plus 1 year of experience in the job offered or 1 year of work experience in data science, analytics, business, mathematics, economics, computer science, or other quantitative fields such as engineering/operations research, in an analytical, quantitative, or technical role in lieu of a Master's degree plus 4 years of experience.

Requirements 

The position requires experience with: Three (3) years of that experience or coursework should be gained in the following skills (skills can be gained concurrently with education): computer-aided decision support (utilize computer programs or packages to analyze data and support business decisions), or any analytical/modeling language (e.g., Python, R, SAS, or SQL), and data visualization tools like Tableau, PowerBI, Spotfire, etc. The position also requires experience with: Subject matter expertise in descriptive, diagnostic, predictive and prescriptive modeling knowledge and skills. Advanced problem-solving abilities. Subject matter expertise in analytical/modeling language knowledge. Advanced statistical analysis knowledge, and other quantitative analysis of complex business situations. Ability to communicate highly complex information in an understandable manner to both technical and non-technical audiences at all levels. Ability to regularly prepare and formally present recommendations to leadership. Strong project leadership skills. Ability to mentor lower levels. Utilize computer programs or packages to analyze data and support business decisions. Understanding of business concepts relevant to revenue management, marketing, and finance. Familiarity with relational databases like Teradata and Oracle. Ability to manipulate large data sets using SAS, SQL, Python, C, VB.net, Java, JavaScript, R and Cloud Technology. Familiarity with data visualization tools like Tableau, PowerBI, and Spotfire. Able to perform qualitative and quantitative analytics to predict market response and business impacts. Position allows for telecommuting from home within commuting distance of Harrison, AR.