Data scientist (offline)

We are looking for a Senior Data Science analyst with a passion for both math and technology to join our business analytics team. You must have experience working with large data sets and understand how to manipulate and analyze them using various statistical and mathematical methods.

Responsibilities
• Become familiar with all aspects of the Company’s global operations.
• Establish and execute a vision for the delivery of business intelligence information and analytics solutions to key stakeholders.
• Interface with business customers, gathering requirements and delivering complete reporting solutions.
• Own the design, development, and maintenance of ongoing metrics, reports, analyses, dashboards to drive key business decisions.
• Formulating, suggesting, and managing data-driven projects which are geared at furthering the business's interests.
• Build analytic systems and predictive models
• Work closely with project managers to understand and maintain focus on their analytical needs, including identifying critical metrics and KPIs, and deliver actionable insights to relevant decision-makers
• Develop and maintain databases by acquiring data from primary and secondary sources, and build scripts that will make data evaluation process more flexible or scalable across data sets
• Create and maintain rich interactive visualizations through data interpretation and analysis integrating various reporting components from multiple data sources
• Create systems that monitor inputs and performance on a real-time basis to inform engineers when unexpected changes arise.
• Maintain active research and follow industry trends risk assessment and analytics in general
• Recommend and build new metrics and analysis that enable better perspective on business efficiencies and guest satisfaction.
• Design and develop weekly, monthly, and quarterly dashboards, scorecards and reporting for the team and present insights to stakeholders.

Preferred Qualifications

• Master’s degree; such as Computer Science, Computer Engineering, Machine Learning, Statistics, Mathematics, etc
• 4 years industry experience in applying Computer Science, Computer Engineering, Machine Learning, Statistics or related technical discipline.
• 5+ years of industry experience in developing, testing, and validating credit risk models in the financial services industry
• Expert knowledge with a scripting language (e.g. Python) and with a object-oriented language (e.g. C++, Java).
• Ability to communicate technical concepts and solutions at a level appropriate for technical and non-technical audiences.
• Experience with processing, analyzing, and modeling
• Experience with agile/scrum methodologies
• Experience with big data: extraction, processing, filtering, and presenting large data quantities (100K to Millions of rows) via AWS technologies, SQL, and data pipelines
• Experience applying with either boosted trees models, decision trees, or other models to solve credit underwriting problems
• Strong skills in statistics, probability, and/or machine learning
• A track record of solving problems using data science. The tooling/language isn't important. (e.g., numpy, pandas, scikit-learn, R, etc.)
• Experience with relational databases and SQL
• Strong communication skills and the ability to work with others in a closely collaborative team