Data Scientist, Wisetack

• We are looking for someone who not only possesses deep technical expertise but also has strong business acumen, enabling them to identify the most impactful solutions that align with our strategic goals
• M.S. in Math, Economics, Statistics, Engineering, Computer Science, or other quantitative field
• 2+ years of experience as a Data Scientist with a total of 3+ years of professional experience
• Familiarity with OLS and Logistic regression modeling, as well as familiarity with modern machine learning techniques such as gradient boosting and neural networks
• 2+ years of experience with SQL
• 2+ years of experience with either Python or R (We primarily use Python)
• Demonstrated experience performing analyses that drive business decisions
• Demonstrated experience either deploying ML models into production, or working with an engineering team to do so

Desirable

• As a Data Scientist / Senior Data Scientist at Wisetack, you will play a pivotal role in shaping the future of our consumer lending product by driving data-driven decision-making across key areas, including credit risk, fraud, growth, and product.
• Your work will be essential in designing, building, and deploying predictive and machine learning models, providing prescriptive recommendations, conducting thorough ad hoc analyses, and developing strategic heuristics to solve complex business challenges
• You will have the autonomy to take ownership of problems and craft data-driven solutions that deliver tangible value to our stakeholders
• Collaboration is key in this role.
• You will work closely with cross-functional teams to ensure your solutions are seamlessly integrated into our products and workflows, directly contributing to our mission of building transparent, intuitive consumer lending products.
• Your ability to communicate complex data insights in a clear and actionable manner will be critical to your success
• Develop an understanding of different departments at Wisetack - primarily Fraud, Credit Risk, Product, and Growth - and come up with ideas for how predictive modeling / ML, experimentation, or analytics can be used to improve specific business processes
• Develop data pipelines to operationalize predictive / ML models, in collaboration with our data engineering team
• Monitor and improve predictive / ML models that have already been deployed
• Present your work to stakeholders, including executive leadership, of varying degrees of technical expertise
• Write clear, thorough documentation of your work, including your thought process, and future opportunities for improvement where applicable