Data Science Advisor-Marketing

Job Description

• Under limited supervision provides expertise and leadership at the enterprise level related to vast quantities of data, enterprise analytics, statistical modeling, and artificial intelligence (AI)/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 analytical solutions to relatively less well-defined and highly complex business problems
• 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 teams in advanced descriptive, diagnostic, predictive and prescriptive modeling, advanced statistical analysis, and other quantitative analysis of complex business situations
• Makes advanced use of current and emerging technologies to evaluate trends and develop actionable insights and recommendations to business partners and management
• Makes advanced 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 management
• Provides consultation to management on a regular basis
• Routinely works on multiple complex assignments concurrently
• Mentors less senior staff

Minimum Qualifications:

• Master's degree in data science, analytics, business, mathematics, economics, computer science or other quantitative fields such as engineering/operations research
• Three (3) years 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
• Two (2) years of experience or coursework with 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.
• Strong problem solving, analytical, and communication skills
• Directly related advanced degrees may offset experience requirements

Skills/Knowledge/Experience Considered a Plus:

• The employee is expected to develop useful and insightful information using rigorous advanced analytical approaches and a variety of data sources using the computer skills (Python Programming, SAS, Unix, SQL, Azure Cloud computing, etc.) in job functions such as:
• Data Engineering: Data extraction/querying: write/modify queries to extract data from internal/external databases in various environments such as mainframe, UNIX, Oracle, Teradata, SAS, Python, Azure tool set; transferring of data between various environments;
• Data wrangling and feature engineering: Data validation and methodology development: evaluate data quality; develop advanced methodologies and optimization approaches perform functions including data cleansing, formatting, merging
• Data processing and analysis: use tools such as Azure or Python or SAS or SQL, perform functions synthesizing, advanced statistical analysis and machine learning (such as linear regression, logistic regression, ANOVA, chi-square, f-test, t-test, principal components, factor analysis etc.), predictive modeling and data mining techniques to fully understand customer behavior and preferences;
• Generating business insight: analyze/research data and get actionable insights with business acumen to explore patterns and trends; detect and identify anomalies, investigate and interpret findings to gain business intelligence and insight;
• Analytic reporting and storytelling: summarize data to produce reports and deliverables that provide actionable insight and recommendations to support key organizational strategies;
• Database/System design: design and create databases and systems that utilize internal and/or external data, including user interfaces for these databases, to support internal analyses and processes. Document, organize and maintain data files;
• New/advanced approaches: generate new advanced quantitative, scientific and statistical approaches to business analysis related to customer analysis, market analysis and forecasting in support of the enterprise’s global strategies. Research new data sources and tools to enhance productivity and statistical modeling capabilities.

Job Specific Information:

• Assists in synthesizing analytical views from various business dimensions in support of business decisions based on business plans, actual or forecast enterprise performance, products, channels, automation types, industry, competition, market and customer segments
• Determines go-to-market tactics related to specific target customers, markets and products in term of marketing communication and sales calls
• Typically works in tandem with peers from other groups.
• Independently attends cross-functional meetings and discussions to understand analytical requirements across enterprise business functions
• Demonstrates excellence in computer aided decision support (utilize computer languages or packages to analyze data and generate reports, presentations or insights in business, mathematics, economics, computer science, or other quantitative field such as engineering/operation research) and programming languages (e.g. SAS, SQL, Python, C, VB.net, Java, JavaScript or R), relational databases (e.g. Teradata, Oracle) or visualizations tools (e.g. PowerBI, Tableau, Spotfire) Mentors and trains professionals in less senior positions within the team on quantitative data analysis. Provides updates and reports to upper management (typically within the department)

Work Location(s)/ Domicile:

• Position will be hybrid in Collierville, TN and candidates must live within a reasonable commutable distance. This position is hybrid meaning that employees must be onsite as directed by leadership but allows team members flexibility to work from home otherwise.

Relocation:

Relocation assistance may be available based upon business needs.