Senior Data Scientist

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, projectmanagement, user experience design, software development and digitalmarketingExperience in establishing data technology foundations for agile businessintelligence, data lakes and data workbenches, and applied machine learning/AIExperience with large-scale data analysis technologies (e.g. Relational andNoSQL data stores, Spark framework, and cloud development in the AWSEcosystem)Specializations and applied experience in the following areas:Consumer Credit and Risk ModelingFraud and Anomaly DetectionCustomer Segmentation and Intent ModelingMarketing Attribution and TargetingRecommendation EnginesOriginally posted on Himalayas

Apply Now