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Investment Data Scientist, Global Diversified Program

Oxford Properties

This is a Contract position in Toronto, ON posted November 2, 2020.

Why join us?

We are hiring an Investment Data Scientist to help drive advanced data analytics, add value through the use of alternative and unstructured data, and to build visualization tools for optimal interpretability and data-driven decision-making!

Reporting to the Managing Director of the Global Diversified Program, OMERS Capital Markets, you will be instrumental in developing and deploying an advanced data science platform. You will take an innovative approach to using technology to improve research and operational efficiency, open up the boundaries in big data technologies and cloud-based platforms, as well as engineer web-based interactive visualizations to gain investment insights!

As a member of this team, you will be responsible for:

• Developing, operationalizing and deploying sophisticated data science investment tools (such as NLP, AI, and Machine Learning) on alternative data
• Researching strategy improvements such as new factors or enhancements to existing factors, portfolio construction, and risk management
• Procuring data and coordinating maintenance of the data lake (cloud) and database
• Developing tools to automate implementation and back-testing of investment ideas, including feature extraction from large data sets
• Providing domain expertise related to data automation, analytics and visualization tools
• Building and operationalizing data engineering capabilities to centrally ingest structured and unstructured data, eliminating manual transposition to prepare data for analysis
• Remaining on the “leading edge” of data analytics technologies to identify new techniques and providers to meet demand
• Contributing to the research efforts across all strategies within the Global Diversified program

To succeed in this role, you have:

• 3 to 5 years of experience in applying data science (Natural Language Processing, AI, and Machine Learning) within a business environment. Exposure to the investment management or the financial services industry will be considered an asset.
• Strong programming skills (Python, Django, Javascript, Vue)
• Knowledge of SQL, and hands-on knowledge of using Azure and experience with large data sets
• Experience With Machine Learning Frameworks, such as TensorFlow , PyTorch or Spark MLib
• Exposure to data modeling, data architecture, data engineering, data analysis and data science (familiarity with ETL tools, data warehousing and big data architecture and cloud constructs)
• An undergraduate degree in computer science, engineering or finance and a consistent track record of strong academic and extracurricular achievements
• Excellent analytical skills and a high attention to detail
• Commitment to learning and intellectual curiosity, with a passion for investing
• Excellent interpersonal skills, with strong written and verbal communication skills