Kapitus is one of the most reliable and respected names in small business financing. As both a direct lender and a marketplace of trusted lending partners, we provide small businesses the funding they need, when and how they need it.
We have spent the past 15 years building a culture that makes us excited to come to work in the morning. Our company is fast paced, teammates need to be self-directed and have an internal motivation to do the right thing, even when the right thing takes a lot of hard work.
We show our teammates our appreciation by offering great benefits, competitive pay, and solid opportunities for growth.
- Build predictive models including but not limited to marketing, credit risk, fraud, and offer acceptance propensity.
- Collaborate to build a Marketing prospect database, and associated models and campaign designs.
- Work with the Risk team to implement policy and pricing decisioning rules.
- Perform through testing and validation of models and support various aspects of the business with data analytics, I.e., experience with data and model governance.
- Identify new data sources/patterns that add significant lift to predictive modeling capabilities; ideally come in with existing knowledge about relevant datasets/services to leverage.
- Research, design, implement and validate cutting-edge algorithms/models to analyze diverse sources of data to achieve targeted outcomes, I.e., be up to date on data science research (papers and libraries); be able to build and evaluate models yourself.
- Conduct analysis and turn insights into actionable changes for predictive models or policies; have experience identifying and prioritizing the business impact.
- Recommend ongoing improvements / tuning to methods and algorithms currently in use/production.
- Deliver informative and effective findings, results, and recommendations from statistical analysis to stakeholders, both technical and non-technical audiences.
- Effectively mentor non-statistical programming peers about statistical programming practices.
- MS in Statistics, Economics, Finance, Survey Research or another related quantitative field.
- Strong understanding of Computer Science fundamentals.
- 4+ years Statistics/data modeling in an applied context.
- Proven track record of building new models and improving existing models.
- Strong attention to detail; excellent communication and project management skills.
- Thorough understanding of statistical modeling techniques.
- Advanced Python or R; we are a primarily-Python shop.
- Exploratory data analysis and visualization.
- Experience with marketing mix modeling, digital attribution modeling, multivariate regression, time-series modeling, Bayesian statistics, segmentation modeling, machine learning, data mining, simulation, optimization, forecasting.
- Have a portfolio (e.g., website, github, paper references, etc.) of papers, visualizations, or software.
- Profession experience at a financial services organization
- Econometric modeling, traditional modeling techniques (regression, tree-based models), deep learning
- Agile, Scrum experience
- Salesforce, HubSpot
- Strong SQL; we primarily use MySQL
- Big data: e.g., competence with Spark, Redshift or Snowflake
- Linux, AWS