Sr Data Scientist

HRB; Toronto; On-site; CAD 80,000 - 120,000; Full time

Job summary

An innovative firm is looking for a Data Scientist to join their dynamic team. This role involves developing cutting-edge machine learning models to enhance fraud detection and member protection. You will collaborate with a talented group of engineers and data scientists to create a robust data science automation framework. Opportunities abound for research and application of the latest machine learning techniques, making this position ideal for those passionate about pushing the boundaries of technology. If you thrive in a collaborative environment and are eager to tackle complex challenges, this is the perfect opportunity for you.

Qualifications

• 5+ years of experience with 2+ years in a Senior Machine Learning role.
• Strong understanding of analytical and machine learning methods.
• Proficiency in machine learning frameworks and libraries.

Responsibilities

• Design and build machine learning models to detect fraud.
• Collaborate with partners to deploy models and strategize.
• Lead predictive modeling projects using data mining techniques.

Skills

Machine Learning

Python

Data Analysis

Keras

TensorFlow

PyTorch

SQL

PySpark

Graph Analytics

Fraud Risk Management

Education

Bachelor's in Computer Science

Master's in Computer Science

Ph.D. in Computer Science

Tools

Keras

TensorFlow

PyTorch

scikit-learn

SQL

PySpark

Job description

Who are we?
We apply big data, artificial intelligence, and machine learning to bring the next generation of financial products and services to global markets.

Position Summary:
We are seeking a Data Scientist to develop large-scale big-data machine learning and solution automation toolkits and libraries. You will collaborate with a talented engineering and data science team to create a state-of-the-art data science automation framework that supports numerous solutions and users. Additionally, you will have opportunities to research the latest machine learning techniques from industry and academia and incorporate them into our data science community.

What does this include?

• Design, build, evaluate, and defend machine learning models to detect various types of fraud, focusing on member protection.
• Collaborate with business partners to deploy models and strategize using model results.
• Develop and implement metrics to monitor and measure the impact of models and strategies.
• Perform full cycle model design and development, including identifying objectives, sampling, testing/validation, calibration, and performance monitoring.
• Lead predictive modeling projects using data mining techniques to estimate member engagement, operational performance, or other business outcomes.
• Utilize Link Analysis/Graph analytics to identify and mitigate deeply-connected fraud networks and detect new accounts added to these networks.
• Apply unsupervised learning methods to augment existing models or detect portfolio anomalies.

Requirements:

• 5+ years of overall work experience and 2+ years as a Senior Machine Learning Engineer or similar role.
• Strong understanding of advanced analytical and machine learning methods.
• Proficiency with machine learning frameworks (Keras, TensorFlow, PyTorch) and libraries (scikit-learn).
• Passion for learning state-of-the-art machine learning frameworks and algorithms.
• Solid understanding of computer science fundamentals, data structures, and algorithms.
• Experience with object-oriented design and application development in Python.
• Familiarity with Big Data technologies (SQL, PySpark).
• Creative thinking and willingness to challenge norms.
• Hardworking attitude with a fun approach.
• Strong teamwork and collaboration skills.
• Experience in fraud risk management is a plus.
• Knowledge of Scala is a plus.
• Educational background: BS, MS, or Ph.D. in Computer Science or a related technical field.
• Ability to handle high-pressure situations and a proactive, hands-on approach.