As a data scientist, you will work with us to solve challenging business problems and develop effective data-based solutions that enable us to deliver quality and affordable housing. Our data science team prides itself at problem-solving at the highest level and partnering with our business groups to deliver high-quality data solutions that hit the mark for our business groups.
What You Will Do
- Serve as a core contributing member of challenging and strategic data science projects undertaken by AIDA. You will engage in high impact problem-solving exercises, assist in the selection and implementation of algorithms, support project management efforts, fand be responsible for the correctness, efficiency, and integrity of your team's solutions.
- Contribute to the team’s technical workflow, processes, and methods. You will be responsible for organizing your team’s efforts, uplifting overall practices where possible, and reviewing the work of your peers to ensure high standards and conformity to best practice.
- Engage key stakeholders from IT and business units to co-create high-impact and high value solutions for HDB. This involves frequent engagement and building of effective partnerships with technical units like system project leaders and data engineers, and our business units.
- Stay at the cutting edge of data science innovations by actively surveying the DSAI landscape and consistently uplifting your technical proficiency.
Pre-Requisites for the Role
- 3+ years of active data science work with a reputable employer.
- Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative discipline.
- High proficiency in problem-solving for data science (e.g., with suitable frameworks like MECE, root cause analysis, etc.).
- Familiarity in MLOps as a framework, with strong experience of end-to-end model development and deployment in the cloud (e.g., AWS).
- Seasoned in the theory and execution of deep learning algorithms and architectures (e.g., transformer models, reinforcement learning), AI Engineering (e.g., neural embeddings, LLM models, building of GenAI systems with frameworks like LangChain and LangGraph, vector databases, EDD, etc.), optimization, statistical modelling, and multi-criteria decision analysis.
- Experience with data engineering for data science (e.g., ELT concepts, structured table transformation experience, database technologies, etc)
- Strong team player
- Superb communication and visualization abilities.
- Strong programming and development skills in Python (and accompanying frameworks), R, SQL, Shell scripting