A Singapore-based start-up, JobKred uses Big Data and AI to scan online labour market information to decode the relationships between jobs and skills and understand the latest developments in the world of work. With this information, JobKred provides both local and global businesses and enterprises with a workforce transformation platform. Using the digital platform, business leaders can identify future-ready skills and create dynamic competency frameworks to guide their employees’ personal development. They can also get a real-time pulse on the skills inventory of the organisation’s talent pool and empower their employees with AI recommendations to personalise their learning and receive career recommendations.
- Growing the Organisation’s data analytics and AI capability
- Develop and maintain a data pipeline of large-scale data indexing.
- Engage in both exploratory analysis and predictive models to identify data trends and anomalies.
- Explore new hypotheses, build deep learning algorithms and be responsible to maintain model quality over time.
- Take ownership of the algorithmic structure and explain complex deep learning algorithms in layman terms to business stakeholders or tech talks.
- Ability to set and achieve project objectives & milestones.
- Document analytical findings for technical teams, executives or publication.
- Ph.D. or Masters in Natural Science, Computer Science, Data Science, Statistics, Mathematics, or equivalent fields.
- At least 3-5 years of relevant working experience in similar fields.
- Proficient in Python and SQL languages.
- Ability to handle text manipulation tasks such as processing and parsing.
- Understanding of recommender systems such as collaborative filtering and content filtering.
- Experience in using machine learning libraries such as Scikit-learn, Tensorflow, Keras or Pytorch
- Experience in model hyper-parameter tuning, embeddings and feature engineering.
- Experience in natural language process (NLP), statistical modeling, network analysis, and data mining techniques
- Love minimal, beautiful code and neat documentation.
- Team player, both internal between data scientist as external with business stakeholders
- Plus: Experience with cloud computing (AWS/GCP/Azure)
- Plus: Deep Learning (RNN, LTSM, XGBoost)
- Plus: Continuous deployment (CI/CD)