🕒 13 days ago
As a Data Scientist II in the Fraud & Risk team, you will design and implement advanced deep learning models to enhance fraud detection and risk management.
Data Scientist
📅 Jan 6
Machine LearningStatisticsComputer SciencePython
📜 Description
- Work on data science projects using structured and unstructured data.
- Implement and productize scalable machine learning models for production.
- Build data products that extract valuable business insights.
- Prototype methods from cutting-edge research papers.
- Apply critical thinking and problem-solving to data science challenges.
🛠️ Requirements
- BS (or higher, e.g., MS, or PhD) in Computer Science or related engineering field involving coding
- Experienced implementing and scaling machine learning models in production environments
- Strong understanding of machine learning theory
- Hands on experience with Statistics
- Capable of quickly implementing prototypes of cutting-edge research papers
- Proficient in Python (i.e. Pandas, Numpy, scikit-learn, etc), R, TensorFlow, amongst other data science related tools and libraries
- Analytical mind and strong business acumen
✨ Benefits
- Competitive compensation.
- Accountability-focused environment without micromanagement.
Full job description
Company Description
You will join a world-class team of engineers and data scientists from Facebook, Uber, Amazon and Google. We are a fast growing consulting firm based in Toronto with clients ranging from leading startups building impactful technologies to Fortune 500 companies looking to scale their engineering and data capabilities.
Job Description
We are looking for Data Scientists who are passionate about Machine Learning, and have deep knowledge in Statistics and Computer Science. You enjoy doing data science projects with structured and/or unstructured data and are motivated to productize scalable machine learning models. We will also rely on you to build data products to extract valuable business insights. Critical thinking and problem-solving skills are essential for this role.
Qualifications
- BS (or higher, e.g., MS, or PhD) in Computer Science or related engineering field involving coding
- Experienced implementing and scaling machine learning models in production environments
- Strong understanding of machine learning theory
- Hands on experience with Statistics
- Capable of quickly implementing prototypes of cutting-edge research papers
- Proficient in Python (i.e. Pandas, Numpy, scikit-learn, etc), R, TensorFlow, amongst other data science related tools and libraries
- Analytical mind and strong business acumen
If you're passionate about data science and is hungry to learn, please apply!
Additional Information
We have competitive compensation.
Work on cool projects based on your interests and skills. We believe in accountability and NOT micro-management.
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