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.

Responsibilities:

  • 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.

Qualifications:

  • 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.

Desirable Experience:

  • 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