80470
Permanent/Direct Hire
3 weeks ago
Position title: Data Scientist
Location: Downtown Toronto – Hybrid 3 days a week (Tues-Thurs)
- Writing software to extract, clean, and investigate large, messy data sets of numerical and textual data
- Building and maintaining machine learning models (Gradient Boosting Machines, Neural Networks, etc.) from development, validation, through to deployment in production
- Designing rich data visualizations to communicate complex ideas to customers or company leaders
- Designing and analyzing experiments to optimize business strategies
- Investigating the impact of new technologies on the future of digital banking and the financial world of tomorrow
The Ideal Candidate will be:
- Curious: You ask why, you explore, you’re not afraid to share your disruptive ideas. You know Python and are constantly exploring new open source tools, and hitting up stack overflow on a regular basis.
- A Wrangler: You know how to programmatically extract data from various databases and APIs, bring it through a transformation or two, and model it into human-readable insights (Matplotlib, Seaborn, Tableau, etc.).
- Creative: Big, undefined problems and petabytes of data don’t frighten you. You’re used to working with abstract data, and you love discovering new narratives in unmined territories.
- Proactive: You want to share your knowledge with your peers and contribute back to inner/open source projects which you might consume.
- An Expert: You have superpowers you can’t wait to share. You have expertise in key aspects of model development, model deployment, or inference such that you are the go-to person in those areas.
- An Emerging Leader: You feel comfortable running point on big, complex projects. You know how to motivate others and bring them along your journey. You can paint a compelling picture of your recommendations and manage the message toward both technical and non-technical audiences.
Benefits
- Your choice of hardware – latest MacBook Pro or HP EliteBook and all the monitors you want!
- With Manager approval, you can travel to a conference of your choice annually – PyCon, PyData, AWS re:Invent, KDD, etc.
- Various internal training opportunities across our US and Canada locations
- $5000/yr education budget
- Hybrid work environment with flexible work hours, dress code, and environment
Basic Qualifications:
- Bachelor’s Degree in a quantitative field
- At least 3 years of experience in open source programming languages for large scale data analysis (Python, R, or Scala)
- At least 3 years of experience with version control system like GitHub
- At least 3 years of experience with machine learning or predictive modeling (scikit-learn, H2O, XGBoost, TensorFlow, etc…)
- At least 3 years of experience with relational databases and programming in SQL
Preferred Qualifications:
- Master’s Degree or PhD
- Experience working with AWS (EC2, S3, Lambda, RDS, etc.)
- Experience working with advanced Git Workflows (Pull Requests, Code Reviews, Issues, and Branching)
- Experience writing unit tests and integrating with CICD tools (Jenkins, CircleCI, etc.)
- Experience with experimental design
- At least 5 years’ experience in Python or R
- At least 5 years’ experience with machine learning / predictive modeling (scikit-learn, H2O, XGBoost, TensorFlow, etc.)
- At least 5 years’ experience in SQL