This is a fully remote position, open to applicants in Canada.

• Comprehend the features that influence vehicle pricing and execute processes to forecast future values.

• Design and implement processes and pipelines into a production environment.

• Launch solutions on AWS infrastructure.

• Create tools for monitoring production systems.

• Develop and document various essential production processes.

• Maintain and enhance production algorithms.

• Optimize ETL processes and address evolving data and valuation needs.

• Work in collaboration with technology and engineering teams to establish new processes and enhance existing ones.

• Generate visual reports in Tableau for data validation and review, utilized by both internal and external clients.

• Conduct thorough quality assurance on automotive industry forecasts and the resulting vehicle valuations.

• Assist internal stakeholders in comprehending predictive products and their methodologies.

• Create presentations that make technical predictions accessible to the automotive sector.

• Execute ad-hoc data analysis and reporting tasks.

• Minimum of 2 years of professional experience handling large datasets.

• At least 2 years of professional experience with statistical programming tools (Python/Pandas is required, Spark is preferred).

• Over 2 years of professional experience with database management systems (SQL, RedShift, Hive, MYSQL).

• Familiarity with AWS tools (S3, Sagemaker, Glue, Lambda, etc.).

• Capacity to articulate technical processes to both colleagues and non-technical audiences.

• Master’s Degree in Statistics, Data Science, Economics, or an equivalent field.

• Experience with automotive market analytics.

• Proficiency in deploying CI/CD within cloud-based systems, managing code via Git.

• Experience using Tableau for data visualization tasks.

• Background in prompting and integrating generative AI outputs into workflows.

• Some demonstrable examples of production data pipelines, product deployments, or data visualizations you have developed.

• Experience in deploying machine learning models into production through an API.

• Competitive salary and performance-based bonuses.

• Comprehensive health and wellness benefits.

• Opportunities for professional growth and development.

• Flexible work arrangements and a supportive work environment.

Data Scientist

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