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Oxford Data Plan
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We are looking for a full-time data scientist to work with us on the following areas:
Product deployment – creating, deploying, and maintaining new KPI trackers.
Research – finding, collecting, and evaluating new data sources, developing new experimental product features for end-users, improving our methodology.
Reporting to the Data Science Manager you will:
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.
Deploying new jobs using Docker and AWS technologies.
Monitoring, debugging and maintaining production code.
To be successful in the role you should have:
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.
Desirable skills
Proficient in web-scraping – at least with requests, ideally with selenium or other web-scraping packages.
Software development – experience in managing installable python packages is very valuable.
Proficient SQL and database knowledge and experience.
Advanced knowledge of time-series modelling or Bayesian statistics.
Experience working with AWS.
Experience creating visualisations with Power BI.
Proficiency with Git.
Experience/proficiency with Docker.
Good experience/knowledge of the finance sector.
Applicants should be fluent in English and have an interest in Finance and Data Science.
After you apply, unlock the direct contact details of the people who actually make the call. A quick follow-up makes you 5x more likely to land an interview.
Marcus Rivera
Chief Revenue Officer

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