What are the responsibilities and job description for the Platform Analytics position at Disney Experiences?
Job Details
The Customer Engagement (CE) team delivers powerful customer experiences across marketing touchpoints by using data and tools to bring marketing to life. The CE Analytics - Manager I will report to the Manager, CE Advanced Analytics who leads both the Advanced Analytics and Business Intelligence functions within the Customer Engagement - Direct Channel organization.
Overview
This Data Science-focused role on the CE Advanced Analytics team consists of the following functions: Developing analyses, predictive models, self-service end-user tools, dashboards, and workflows demonstrating Machine Learning algorithms and innovative technologies such as Snowflake, Dataiku, and Tableau. This role will also work with multi-functional partners to showcase insights while recommending applications that advance CE Marketing and Audience strategies. This role will also lead the development of plans, communications, and timelines for individual projects using the Agile framework.
Solutions
Consulting
QUALIFICATIONS
We are looking for demonstrated experience applying data science modeling techniques and proper statistical testing methodology to guest behavior (resorts, cruises, theme park tickets, merchandise) and Marketing engagement. We desire someone who is comfortable planning, researching, and creating solutions.
#LI-VT1
#DXMedia
#DXMarketing
Overview
This Data Science-focused role on the CE Advanced Analytics team consists of the following functions: Developing analyses, predictive models, self-service end-user tools, dashboards, and workflows demonstrating Machine Learning algorithms and innovative technologies such as Snowflake, Dataiku, and Tableau. This role will also work with multi-functional partners to showcase insights while recommending applications that advance CE Marketing and Audience strategies. This role will also lead the development of plans, communications, and timelines for individual projects using the Agile framework.
Solutions
- Build predictive models on guest behavior; examples include: likelihood to purchase, likelihood to engage with a marketing message, or estimating spend
- Design and conduct statistical experiments (ex. A/B testing) to measure the efficiency of our audiences
- Mine for insights by using exploratory data analysis or interpreting model results
- Develop self-service end-user tools and dashboards to help partners understand audience behavior, audience performance and contactibility
- Promote products to production and maintain products in production to ensure availability in activation
Consulting
- Work with cross-functional partners to find efficiencies, understand requirements and goals, deliver optimal products, and implement.
- Find opportunities to develop or use analytics to meet a business objective
- Work with technical partners to source new data or resolve issues with existing data
- Showcase insights and educate partners on developed products, which highlight advancing CE strategies and contributions.
- Develop plans and timelines for individual projects by working in agile framework to deliver work products in sprints. Leverage tools such as Jira and Airtable to track and catalog work, and communicate progress to direct leadership.
QUALIFICATIONS
We are looking for demonstrated experience applying data science modeling techniques and proper statistical testing methodology to guest behavior (resorts, cruises, theme park tickets, merchandise) and Marketing engagement. We desire someone who is comfortable planning, researching, and creating solutions.
- Bachelor's degree in Data Science, Statistics, or similar degree
- 2 years of experience using programming languages (Python or R preferred) to build predictive models and to conduct statistical testing with sound experimental design
- 2 years of experience using SQL (Teradata, Hive, or Snowflake)
- 2 years of experience with Machine Learning algorithms and statistical methods including classification models such as logistic regression and decision trees, and segmentation models such as clustering and scoring.
- Experience using Machine Learning platforms such as Dataiku, DataRobot, or Databricks
- Experience communicating technical work to non-technical partners
- Experience using the following machine learning libraries: Scikit-Learn, MLLib, or H2O.ai
- Experience using Tableau, Microsoft Power BI, or Qlik
#LI-VT1
#DXMedia
#DXMarketing
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