Credit risk modelling data scientist developing and maintaining models for Desjardins. Guiding risk quantification, credit decisions, compliance, and practitioner - led modelling projects.
About the role
- Data Scientist at Dropbox partnering with product, engineering, and design teams for analytics and business growth. Focusing on revenue growth, product optimization, and launching high-impact initiatives.
Responsibilities
- Develop a deep understanding of customer journey phases and key business metrics
- Perform analytical deep-dives to analyze problems and opportunities, identify the hypothesis and design & execute experiments
- Inform future experimentation design and roadmaps by performing exploratory analysis to understand user engagement behavior and derive insights
- Create personalized segmentation strategies leveraging propensity models to enable targeting of offers and experiences based on user attributes
- Identify key trends and build automated reporting & executive-facing dashboards to track the progress of acquisition, monetization, and engagement trends
- Extract actionable insights through analyzing large, complex, multi-dimensional customer behavior data sets
- Monitor and analyze a high volume of experiments designed to optimize the product for user experience and revenue & promote best practices for multivariate experiments
- Translate complex concepts into implications for the business via excellent communication skills, both verbal and written
- Understand what matters most and prioritize ruthlessly
- Work with cross-functional teams (including Data Science, Marketing, Product, Engineering, Design, User Research, and senior executives) to rapidly execute and iterate
Requirements
- Bachelors’ or above in quantitative discipline: Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field
- 3-5 years experience using analytics to drive key business decisions; examples include business/product/marketing analytics, business intelligence, strategy consulting
- Proven track record of being able to work independently and proactively engage with business stakeholders with minimal direction
- Significant experience with SQL and large unstructured datasets such as Hadoop
- Deep understanding of statistical analysis, experimentation design, and common analytical techniques like regression, decision trees
- Solid background in running multivariate experiments to optimize a product or revenue flow
- Strong verbal and written communication skills
- Proficiency in programming/scripting and knowledge of statistical packages like R or Python is a plus
Benefits
- Health insurance
- 401(k) matching
- Flexible work hours
- Paid time off
- Remote work options
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