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Training Day: A Reskill Resource Recommender�

Filling skills gaps toward low-automation-risk careers

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T(D)areq – Designer David – Developer Daniel – Data Dude

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Two User Journeys

  • Select dream jobs or sector of interest
    • Output required skillset &highlight user’s skill gap
    • Skills link to educational resources (nearby institutions, MOOCs)

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  • Request recommendations (display % overlap)
    • Output high matches:
      • Overall sector
      • Job titles

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User Journey

  • Snape wishes to be a Defense professor
  • Magicks-in his user profile [education, skills, experience]

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Level 1 design:�Request Next Steps

  • Snape already knows his dream job

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  • Filters search results in nested dropdowns:
    • Disciplines: {Dark Arts, Necromancy, Blood Magic}
    • Location: {England}

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Defense Professor

Mocking Students in English

University

[Program of Education]

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Defense Professor

Mocking Students in English

University

[Program of Education]

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Defense Professor

Mocking Students in English

University

[Program of Education]

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Defense Professor

(Desired Match)

University

[Program of Education]

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Defense Professor

(Desired Match)

University

[Program of Education]

Skills Gap

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Defense Professor

(Desired Match)

University

[Program of Education]

Potions Master

(Suggested Match)

Top Matches

→

Skills Gap

Skills Gap

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Top Matches

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Top Matches

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Future prospects:

  • Elaborate profile input
    • Input education → skills constellation updates
    • Resume scraping
    • Searchable/nested dropdowns

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Future prospects:

  • Elaborate profile input
    • Input education → skills constellation updates
    • Resume scraping
    • Searchable/nested dropdowns
  • Recommender matches user profiles to hottest job skills

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Match function elaboration

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Future prospects:

  • Monetization options:
    • Career counseling services
    • Mentor/mentee premium accounts
    • Links to MOOCs, other resources

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Future prospects:

  • Monetization options:
    • Career counseling services
    • Mentor/mentee premium accounts
    • Links to MOOCs, other resources
  • Future research:
    • Investigate data sources
    • Implement recommender

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Recommender elaboration

  • Penalize automatable jobs
  • Incorporating work experience, personal desires

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Recommender elaboration

  • Penalize automatable jobs
  • Incorporating work experience, personal desires
  • Surveys of professionals & success stories
  • Career path trends e.g. LinkedIn data

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Recommender elaboration

  • Penalize automatable jobs
  • Incorporating work experience, personal desires
  • Surveys of professionals & success stories
  • Career path trends e.g. LinkedIn data
  • Valuing skillsets by desirability

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Tareq

web design ∙ javascript ∙ web scraping ∙ shortcuts!

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David

java ∙ client-server ∙ file I/O ∙ data structures ∙ shortcuts!

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Daniel

web scraping ∙ data cleaning ∙ top-down design ∙ new shortcuts!

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Show us what you got!