Overview
The Data Scientist will be responsible for development and execution of advanced analytic models and methods. The position will span multiple brands and marketing teams locally and globally in an effort to influence customer behavior across a multitude of marketing channels.
The Data Scientist will be responsible for understanding industry trends in both analytical methods and data augmentation to drive positive shifts in customer behavior for our clients.
A successful candidate will have a demonstrated track record in applied analytic modeling, machine learning and algorithms. A candidate will have an edge if they are able to show examples of analytic initiatives in their career tenure.
Overall, the position requires extensive ability to plan, develop and execute advanced analytic methods across a multitude of leading brands with large analytic databases. Furthermore, outstanding written and verbal communication, creative problem solving and ability to manage multiple responsibilities and deliverables is required. Must be able to develop strong relationships with agency offices, partners, and team members.
Responsibilities
- Reporting to the Director of Analytics and working closely with cross-functional team members, provide delivery of analytics services including:
- predictive modeling
- machine learning
- segmentation
- time-series forecasting
- Create dashboards and visualizations of processed data
- Communicate unique insights or issues uncovered through working with the data
- Proactively identifies potential data enhancements and augmentations from external data provides
- Use predictive analytics and machine learning to drive business decisions
- Support the development of measurement strategies, identifying key metrics to track and report on
- Delivers hands-on strategic modeling activities such as customer segmentation, targeting strategies, lifetime value, in-market timing, loyalty, response/engagement optimization, machine learning and quantitative support for ROI analyses and other modeling activities
- Work directly with client service and technical teams, and potentially directly with clients, to identify modeling goals
- Tracks and reports on our initiatives, successes, and lessons learned, and packages outcomes in an client facing presentation
- Prioritize tasks and work assignments, ensuring timelines and commitments are met
- Participates in ad hoc special projects as required, and other tasks as assigned
- Manipulate, cleanse and perform statistical analyses
Desired Skills & Experience
- Minimum 1-3 years’ experience in delivering analytic results working within database marketing, CRM and analytics ideally in the marketing field
- Post-secondary education in a relevant field including Mathematics, Statistics, Computer Science or equivalent experience
- Classification methods (e.g., Logistic Regression, Decision Trees, Neural Net)
- Regression methods (e.g., Linear, Nonlinear, Boosted Regression Trees)
- Time-series Modeling (e.g., ARMA, GARCH, Exponential Smoothing)
- Experience in measurement and analysis of data from business and marketing perspectives
- At least one years’ experience in hands-on use of tools such as R, Python, or SAS
- Experience cleansing, manipulating, and transforming data
- Analyst will also have experience creating and conducting dynamic presentations
- Experience in any of the following: business strategy and presentation, financial analysis, and/or consumer market research would be an asset
- Expertise with business intelligence tools and supporting technologies
- Highly organized with an ability to work under tight deadlines and shifting priorities
- Excellent oral and written communication skills
- Experience working in a SQL server environment
- Highly professional and presentable with a strong business acumen
- Automotive and digital experience strongly preferred
Benefits
The Marketing Store provides comprehensive benefits offerings to all full-time employees starting on day one. Our benefits include options for medical and dental insurance, 401(k) plan with Company matching provision, profit sharing, flexible spending accounts, tuition reimbursement, life insurance, health and wellness benefits (including discounts on products & services), employee assistance program, and disability insurance