CARPROOF is a growing, fast-moving environment where data is the foundation of who we are and what we do. The Data Scientist will be responsible for the creation of innovative and exciting new products and services in CARPROOF’snewly formed Advanced Analytics Garage. The successful candidate will have a strong ability to execute efficient data preparation to develop and apply predictive and prescriptive data science models.
The CARPROOF Advanced Analytics Garage is a division of the Product Management team with a mandate to use advanced analytical techniques to build innovative products and solutions for the automotive industry. The Advanced Analytics Garage is where thought leadership and data science come to life inside CARPROOF’s products and services.
- Design and build products for the automotive industry through data science and advanced analytical models
- Work with Development teams to deliver and implement advanced analytical models, and R/Python scripts and libraries for the development of new products
- Lead the data cleansing and ETL processes for modelling purposes
- Work with Product Managers and other key business stakeholders to execute against the product roadmap
- Occasionally assist in ad-hoc strategic initiatives, such as pricing or resource optimization
- Work with the Data Management team to recommend ways to improve product data quality, reliability and consistency
- Find new applications for existing product data, and identify and communicate data acquisition needs
Education, skills and experience required
- Degree in Computer Science, Applied Mathematics or Statistics, Master’s preferred
- Expertise in ETL, data cleansing and data blending is crucial
- Expert understanding of, and ability to work with, relational data models
- Must be fluent in programming languages R and SQL; Python and NoSQL are assets
- Experience with SPSS, Alteryx, Tableau, Power BI analytics and visualization tools is an asset
- Advanced user of data science techniques such as:
- Multi-variate regression
- Linear and non-linear regression models
- Generalized linear models
- Penalized regression models: LASSO, Ridge and cross-validation
- Decision trees/random forest
- Clustering and classification
- Hypothesis testing
- Bayesian statistics
- Model fitting and validity checking
- Ability to apply the above techniques to practical issues
- Experience creating machine learning models
- Experience in text analytics and natural language processing is an asset
- Exposure to product management in an Agile development environmentis an asset
- Passion for using data science to solve problems
CARPROOF’s core values are: Be the solution, embrace change, commit and deliver and powered by passion. The successful candidate will share these values.
Compensation includes base salary commensurate with experience, performance bonuses, health/dental benefits and an optional RRSP matchingprogram.