Learning Systems Data Scientist & Administrator

Job Description

The Learning Systems Data Scientist and Administrator reports to the Sr. Director of Sales Education and Commercial Effectiveness.  This position will play a key role in the development and administration of a new digital learning ecosystem that will leverage data science and a cloud-based Learning Experience Platform (LXP). An LXP enables formal, informal, social, and microlearning, content authoring and management tools and gives learners access to in-depth analytics in their learning process.  By leveraging your data science skills across multiple Siemens Healthineers learning and operational platforms (such as CRM and others) you will help us discover the information hidden in vast amounts of data and provide learners with insights and personalized learning path recommendations. 

Responsibilities

Data Science

  • Apply data mining techniques, conduct statistical analysis, provide reporting and data visualization on learner performance, trends and gaps and other learning analytics
  • Collaborate with other system administrators to access & mine learner performance data
  • Build data-driven, high-quality prediction systems to enable personalized learning paths
  • Enhance data collection procedures to include information that is relevant for building analytic systems
  • Use predictive analytics to the measure and track learning behaviors and outcomes.
  • These insights will enable us to better estimate where to invest in learning and how to improve our learning products to meet business needs.
  • Process, cleanse, and verify the integrity of data used for analysis
  • Provide ad-hoc analysis and present results in a clear manner
  • Stay current on evolving learning technology and data science trends. Provide strategic and innovative recommendations on how to improve processes and outcomes

System Administration

Currently Siemens Healthineers leverages 2 platforms: a Learning Management System (powered by Saba) and a Mobile Sales Enablement Platform (powered by Allego).

  • Leverage your data science skills to create intelligent automation and smart learning assignments to individual learners based on learning and performance data across multiple platforms (e.g., learning management system, mobile sales enablement platform, competency and performance evaluations, CRM data, etc.)
  • Collaborate with IT and Global Sales Education teams to enable automation of user provisioning and group enrollments
  • Upload/test courses created by the Sales Education department, create sessions and curriculums in the system
  • Create competency certifications and assessments in collaboration with the sales education team.
  • Automate curriculum assignments to new hires based on role types
  • Manage other manual learner assignments to existing employees as needed
  • Provide governance/oversight on user roles, group permissions, content management and portal maintenance
  • Manage learning assets (e.g., publish and archive online or blended learning) resources
  • Provide strategic and innovative recommendations on how to improve processes and outcomes

Required Knowledge/Skills, Education, and Experience

  • Bachelor’s Degree in IT, computer science, math, physics, or another related field
  • 3 to 5 years relevant experience in Data Science
  • Technical Experience
    • common data science and visualization tools
    • scripting and programming skills
    • using query languages such as SQL
    • applied statistics skills
    • databases
  • Demonstrated soft skills
    • Adaptability
    • Problem-solving
    • Creativity/Innovation
    • Strategic & critical thinking
    • Communication (oral and written)

Preferred Knowledge/Skills, Education, and Experience

·       Prior experience with administering learning management systems or other platforms is a plus

Travel

This role may require infrequent overnight domestic travel.


*LI-WC1

Job ID: 194994

Organization: Siemens Healthineers

Company: Siemens Medical Solutions USA, Inc.

Experience Level: Experienced Professional

Job Type: Full-time



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