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About the Role
We are seeking a full-time Data Scientist to contribute to product deployment, research, and reporting. This role involves creating, deploying, and maintaining KPI trackers, evaluating data sources, developing experimental features, and improving methodologies.
Responsibilities
- Write robust, commented scripts to collect, clean, process, and save data.
- Analyze data, build, validate, and test prototype models in Jupyter.
- Construct automated pipelines for moving and processing data between different sources.
- Produce data visualisations and dashboards in Python and/or PowerBI.
- Deploy new jobs using Docker and AWS technologies.
- Monitor, debug, and maintain production code.
Requirements
- Proficiency in Python: Ability to write functional, reproducible, and well-documented code.
- Proficient with typical data scientist modules (pandas, numpy, matplotlib, scikit-learn).
- Strong Statistical knowledge: Good understanding of fundamental statistical concepts (e.g., bias, variance, R-squared).
- Good understanding of the theory and practice of linear regression.
- Self-motivated and autonomous individual.
- Significant training and support will be provided; however, we expect a successful candidate to quickly take full ownership of their work and proactively make an impact in ODP.
- Some experience working with databases and using SQL.
- Strong Excel skills.
- Experience with Git.
- Interest in finance.
- Applicants should be fluent in English.
Skills
- Python
- pandas
- numpy
- matplotlib
- scikit-learn
- Jupyter
- SQL
- Excel
- Git
- web-scraping
- requests
- selenium
- Software development
- installable python packages
- time-series modelling
- Bayesian statistics
- AWS
- Power BI
- Docker
- finance sector
Work Type
- full-time