Skilling Data Intelligence Lead

The Global Learning and Skilling team is dedicated to revolutionizing employee skilling through AI-driven, personalized experiences. By integrating diverse learning data with the principles of human motivation, the team strives to create tailored skilling opportunities seamlessly integrated in the flow of work. Thus, readying data for AI processing is a cornerstone of this transformation. 

In this critical role, you will collaborate closely with HR and Engineering teams to leverage AI in identifying essential data sets and converting insights into actionable strategies. These strategies are designed to personalize and contextualize learning, stimulate curiosity, and foster in the flow skill development.  

The Data Skilling Intelligence Lead will assess experiences and evaluate program success and effectiveness to ensure they adapt to the evolving needs of employee skill development. 

Responsibilities

Business Understanding and Impact  

• Understands problems facing projects and is able to leverage knowledge of data science to be able to uncover important factors that can influence outcomes on specific products. Describes the primary objectives of the team from a business perspective. Produces a project plan to specify necessary steps required for completion. Assesses current situation for resources, risks, contingencies, requirements, assumptions, and constraints. Coaches less experienced engineers in standards and practices. Uses understanding of organizational dynamics, interrelationships among teams, schedule constraints, and resource constraints to effectively influence partners to take action on insights. Understands business strategy briefings and articulates data driver strategies for specific industries or cross-industry functions, such as: Sales/Marketing, Operations, and new Data Monetization Schemes. Engages business stakeholders to capture and shape their thinking on data-driven methods applicable to their value chain. Leads customer conversations to understand, define, and solve business problems. 

Data Preparation and Understanding 

• Acquires data necessary for successful completion of the project plan. Proactively detects changes and communicates to leads. Develops useable data sets for modeling purposes. Contributes to ethics and privacy policies related to collecting and preparing data by providing updates and suggestions around internal practices. Contributes to data integrity/cleanliness conversations with customers. 

Evaluating for Insight and Impact 

• Understands relationship between selected models and business objectives. Ensures clear linkage between selected models and desired business objectives. Assesses the degree to which models meet business objectives. Defines and designs feedback and evaluation methods. Coaches and mentors less experienced engineers as needed. Presents results and findings to customer stakeholders.  

Industry and Research Knowledge/Opportunity Identification 

• Uses business knowledge and technical expertise to provide feedback to the engineering team to identify potential future business opportunities. Develops a better understanding of work being done on team, and the work of other teams to propose potential collaboration efforts. Coaches and provides support to teams to execute strategy. Leverages capabilities within existing systems. Shares knowledge of the industry through conferences, white