Data Scientist

We are looking for a full-time data scientist to work with us in our Product Development team. You will be working to create and maintain new KPI trackers. For example, estimating the daily revenue of an e-commerce company, or predicting the number of cars produced by an automotive manufacturer.

You will report to one of our Data Science Managers.

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• Analyze data, build, validate, and test prototype models in Jupyter.
  
• Produce data visualizations in python to inspect correlations and create dashboards with PowerBI.
  
• Deploy new jobs to production using Docker and AWS technologies.
  
• Monitor, debug, and maintain production code.
  
• Conduct equity research on companies and apply domain knowledge to improve models.
  
• Support the Evaluation team by exploring new potential data sources, or building new web scrapers.
  
• Monitor existing KPI trackers to ensure quality.
  

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• Proficiency in Python:
  
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  • Ability to write functional, reproducible, and well documented code.
    
  • Proficient with typical data scientist modules (pandas, numpy, matplotlib, scikit-learn).
    
  
  
  
• Strong Statistical knowledge:
  
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  • 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.
  
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  • 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.
    
  
  
  
• Strong interest in a career in finance or business.
  
• Excellent problem-solving ability and judgment.
  

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• Experience with Git.
  
• Experience working with databases and using SQL.
  
• Strong Excel skills.
  
• Good experience/knowledge of the finance sector.
  
• Proficient in web-scraping – at least with requests, ideally with selenium or other web-scraping packages.
  
• Software development, writing production code.
  
• Advanced knowledge of time-series modelling or Bayesian statistics.
  
• Experience working with AWS.
  
• Experience creating visualizations with Power BI.
  
• Experience with Docker.