Duties & Responsibilities
- Analyze raw data: assess quality, cleansing, structuring for downstream processing.
- Apply the scientific method to data and problems to establish, test and refine hypotheses.
- Visualize and present scientific results effectively for a business audience.
- Design and train accurate and scalable machine learning algorithms.
- Collaborate with the engineering team to bring analytical prototypes to production.
- Generate actionable insights for business improvements (and develop measures to track business improvement).
- Ongoing client interaction to understand their challenges and create solutions.
Desired Experience & Qualification
- Bachelor’s degree or equivalent experience in quantitative field (Operations Research, Statistics, Applied Mathematics, Computer Science, Engineering, etc.)
- At least 1 year experience working with programming (R and/or Python and/or Julia)
- Deep understanding of optimisation, predictive modeling, machine-learning, clustering and classification techniques, and algorithms.
- Fluency in a programming language (e.g. Python,Julia, R,…)
- Familiarity with relational databases, preferably PostgreSQL
- Experience using source control and continuous integration with Git (e.g. Gitlab/Github)
- Preferably some exposure to Linux. Docker / Kubernetes knowledge is an advantage but not required.
- A firm understanding of and experience with the scientific method
- Experience and excellence in data driven storytelling
Desired Skills:
- Data Scientist
- Python
- Julia
- R
- Linux
- Gitlab
- Github
About The Employer:
Join a stable software engineering company and utilise data analysis and conversion skills.