At Kibo, we provide cloud commerce solutions inspired by our clients' needs and designed to empower their teams. Together, we can help them see further, think bigger, and climb higher.
Our software and services include eCommerce, Order Management, Personalization, and Mobile Point-of-Commerce. We serve retailers, manufacturers, and brands, and our solutions are designed to power the shopping experience – from first click to doorstep – and to scale with them as their business grows.
Kibo is seeking a Sr. Data Scientist to help continue to build and innovate our next generation of data-driven applications. You will be part of our Data Science group which develops Kibo’s software for processing large volumes of eCommerce user data into statistical models that drive live applications such as item recommendations, content search and automated statistical testing.
ESSENTIAL RESPONSIBILITIES AND DUTIES:
- Contribute to Kibo’s product roadmap by developing models to solve our customers’ pressing problems
- Develop visualizations that make complex concepts intuitive to nontechnical marketers and merchandisers
- Collaborate with and learn from a like-minded group of data scientists
- Develop models with a variety of requirements (online learning, large data sets, reinforcement learning, recommender systems, etc.)
- Discover, understand, and apply cutting-edge statistical and machine learning techniques with novel applications to e-commerce, marketing, and supply chain problems
- Assist product management and engineering in building full-featured products based on your research
- Assist sales, marketing, and client services in taking products based on your research to market and effectively communicating their value to clients and prospects
- A bachelor’s degree in one or more of statistics, machine learning, math, computer science, economics, quantitative social science or equivalent understanding
- 5+ years of experience in a modern data analysis stack (Python, R, Matlab, SAS, SPSS, STATA, etc.)
- 5+ years of hands on experience with Python and SQL
- Comfortable working in a Linux command line environment
- Effective understanding of how business value, applications, and infrastructure constraints drive modeling decisions
- Ability to implement machine learning techniques in scalable, reliable and maintainable code for real-world software platforms. Experience with AWS Sagemaker preferred.
- Familiarity with software engineering concepts like object-oriented design, software testing, and development lifecycles
- An entrepreneurial mindset, shown by a history of engagement with the end users of a model or the desire to do so.
- Ability to effectively communicate the results and value of models with non-technical stakeholders, both internal and external