Ikigai Data is a careers’ data and insights company. Our mission is to help everyone achieve healthy and fulfilling employment.
Data Science is a key pillar of our company: we build data and tools that help education institutions better support and track the outcomes of their students’ and alumni’s career decisions. We want to democratise access to the data and insights that matter for individuals to make informed career decisions.
To date, we have delivered a pilot for a US-based online training provider and raised an angel equity round to complete product development and satisfy client and partner demands. Our team includes: Gaia Ines Fassò, the founder, with 10+ years’ experience managing client accounts at Accenture and international venture capital fund Anthemis and with previous experience in building and scaling a profit-with-purpose business. Juke Sauerwein is Ikigai Data’s first hire and the Tech Lead: previously an engineering manager at VC-backed no code platform BRYTER and with experience in full stack development, continuous delivery, refactoring and architecture design. We have big ambitions - we want to reach half a million users over the next five years and to get there, we will be growing the company to a diverse team of 13 courageous, thoughtful and entrepreneurial mission-driven professionals.
To date, we have built the data infrastructure and front end solution of JobFit: a web-based application targeted at 16+ students and alumni for logging their education and employment history; identifying skills and skill gaps and exploring viable, less known career destinations and a plan for getting there.
We have secured a pilot with a youth employment organisation supporting 16-21 years-olds from disadvantaged backgrounds and with little career support available to them. To complete product build and to go to market with our pilot, we need to complete the development of the career destinations’ recommendation algorithm.
Currently, we have consolidated and organised data from diverse sources in our MongoDB system, including:
- oNET and ESCO skills and occupation taxonomies
- APIs to job ads boards
- UK government’s open access labour market insights from: https://api.lmiforall.org.uk/
- Web-scraping from UK government’s website https://nationalcareers.service.gov.uk/.
We also will be gathering user-generated data, stored in MySQL, including: users’ career preferences and their answers to a psychometric test available in the app.
Going forward, we want our data to evolve, to incorporate web scraping about trending jobs and skills, contributing to inform how skills and occupation taxonomies should also evolve. And we want to integrate more sophisticated behavioural frameworks in our in-app psychometric assessments, to develop more bespoke career recommendations.
We have the support of a wide CareerTech community and two behavioural and data science programmes that we have been selected for to also help us make this happen. The Data Science hire is now an essential pillar in this growth.
Minimum requirements: Having built reccomendation models and put them in production. Also helpful is experience with clustering, NLP, statistical learning: similarity modeling, collaborative filtering, neural networks etc.
Your responsibility is to design and to ensure the robust delivery of a production-ready recommendation algorithm.
- Design JobFit’s career recommendation algorithm based on Ikigai Data’s structured data and further data sources/resources, including, for example: open access data models and trained datasets
- Support a junior data engineer to build and test the outcomes of the recommendation algorithm with Ikigai Data’s users
- Establish and implement optimisation strategies
- Collaborate with the CEO to ensure the project is delivered to the agreed time and quality standards.
You will not be responsible for building the infrastructure to implement the algorithm, as this will be done by our Tech Lead.
You will have full autonomy in the design of the final solution, in line with Ikigai Data’s business priorities and the insights you built from both data and user insights.
Availability: full time, three months. Starting immediately
Please provide a link to your GitHub or other work examples and let us know why you're interested in the project and in working for a startup.