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Data Scientist

4 weeks ago

Toronto, Ontario, Canada Aviva Full time

Shape the Future of Insurance with Data-Driven Solutions

Aviva Canada is seeking a talented and passionate Data Scientist to join our innovative team at the forefront of using data to revolutionize the insurance industry. You will play a pivotal role in developing cutting-edge fraud detection systems, leveraging machine learning and statistical models to protect our customers and drive business growth.

Your Impact
  • Develop, test, and deploy robust code for data analysis and model building.
  • Transform complex datasets into actionable insights and recommendations, identifying patterns and trends related to fraudulent activities.
  • Design and implement innovative machine learning algorithms to enhance our fraud detection engine, contributing to a more secure and reliable insurance ecosystem.
  • Collaborate with cross-functional teams, including engineers, product managers, and business stakeholders, to ensure seamless integration of data-driven solutions.
  • Continuously monitor and improve existing models, ensuring optimal performance and accuracy in detecting fraudulent claims.
Your Expertise

We are looking for a highly motivated individual with a strong foundation in data science principles and practical experience in developing and deploying machine learning models.

  • Master's degree or higher in Computer Science, Engineering, Mathematics, Statistics, Physics, or a related field.
  • Proven experience (2+ years) in the end-to-end model development lifecycle, working with large datasets and implementing machine learning algorithms.
  • Proficiency in Python programming language, including software engineering best practices such as code reusability and modularity.
  • Strong SQL skills and experience with Git version control.
  • Familiarity with data warehousing concepts, ETL strategies, and cloud computing platforms (AWS) is a plus.
  • Excellent communication and collaboration skills, with the ability to effectively convey complex technical information to both technical and non-technical audiences.