This is a hybrid position requiring presence in Vancouver, BC.
What You'll be doing:
Create data-driven insights in order to enrich the end user experience
Communicate with multiple teams by creating reports in order to share insights and overall data story
Work alongside senior level stakeholders to scope analytics projects to ensure data science deliveries are driving business impact
Evaluate consumer fintech data by using various methods and tools including but not limited to; Machine Learning, Statistics, Data Analysis, Quantitative Finance, and Modern Programming
Facilitate data driven initiatives in the following areas to paint a cohesive data picture:
Customer Segmentation
Underwriting
Lifetime Value Optimization
Financial product development
Fraud and Ethical Lending Analysis
What You Should Already Have:
A Bachelor’s degree in a quantitative field, such as Finance, Computer Science, Economics, Mathematics or a similar technical discipline
5+ years experience in applying analytics, data engineering or data science
Proficiency in working with SQL, Python and/or R across complex real world datasets
Proficiency in using modern data visualization tools, such as Tableau, PowerBI or similar
Experience deploying ML models using machine learning as a service platforms such as Amazon SageMaker, Google Cloud AI, and Microsoft Azure
Excellent written and verbal communication skills
Aptitude for critical thinking as it relates to complex problems and challenge assumptions in order to implement creative solutions
What Would Be Nice To Have:
A Master's degree or higher, focused in data science, analytics finance, or software engineering
Experience applying data science consumer finance, fintech and other Financial Industry domains
Familiarity with related disciplines such as consumer finance, project
management, user experience design, software development and digital
marketing
Experience in establishing data technology foundations for agile business
intelligence, data lakes and data workbenches, and applied machine learning/AI
Experience with large-scale data analysis technologies (e.g. Relational and
NoSQL data stores, Spark framework, and cloud development in the AWS
Ecosystem)
Specializations and applied experience in the following areas:
Consumer Credit and Risk Modeling
Fraud and Anomaly Detection
Customer Segmentation and Intent Modeling
Marketing Attribution and Targeting
Recommendation Engines
