Data Scientist, Loop Returns

• 3+ years of experience in data science, decision science, or similar quantitative fields
• 3+ years of experience with statistical or scripting software such as Python or R applied to data and statistical analysis
• 2+ years of experience writing and optimizing complex SQL
• Statistical modeling and data analysis experience, e.g., significance testing, regression modeling, decision trees, and k-means clustering
• Familiarity with advanced statistical methods (Bayesian, GLM, time series) or machine learning (boosting, CART, neural networks, SVM)
• Experience finding, cleaning, and manipulating data from multiple sources to build analytical data sets
• Experience defining simple, intuitive, and actionable metrics to focus decision-making
• An ability and interest in working in a fast-paced, ambiguous, and rapidly changing environment

Desirable

• As a Data Scientist at Loop, you'll significantly impact our ability to solve merchant problems and fulfill merchant needs.
• Your work interpreting and synthesizing large-scale data and outputs will guide business decisions made by internal stakeholders at all levels.
• You will be successful in this role if you're self-motivated and can run projects independently while collaborating with team members and business stakeholders.
• Success in this role also includes partnering with stakeholders and deep diving into business problems while simplifying and communicating complex analyses into easily accessible and impactful terms in written and verbal formats
• Extract data from various sources, perform exploratory data analysis, and cleanse, massage, and aggregate data
• Develop quantitative analysis, tools, ad hoc reports, and models to support business decision-making
• Utilize statistical concepts and descriptive statistics to understand and describe relationships in data, adding confidence to our analysis
• Build predictive models and complex descriptive analytics, such as segmentations and hypothesis testing
• Partner with Data Engineering and Analytics Engineering to implement analytic insights and recommendations into business processes
• Write high-quality code (i.e., reliable, readable, efficient, testable), provide quality code reviews, and create comprehensive tests and documentation
• Have a good understanding of general business trends and directions to put your work in a broad business context