At Kargo, our mission is to build a connective tissue between the physical world of freight and the digital ecosystem used to manage it. We believe that advancements in smart infrastructure are critical to enabling a safer and more efficient future for logistics.  Our loading dock sensor platform verifies all incoming and outgoing freight, aggregating data that enables shippers and carriers to efficiently manage dock operations, switch out suppliers and understand material flow in real time. 

We care deeply about delivering the best solutions for our customers. As a member of the Kargo team, you will have the opportunity to develop and deploy tomorrow’s hardware & software solutions and help revolutionize logistics.

Responsibilities

• Quantitative analysis – including clustering, regression, pattern recognition, or descriptive and inferential statistics.
• Communicate the results of analysis to product, engineer, and leadership teams to influence strategy.
• Partner with Product, Operations and Engineering teams to solve problems and identify trends, risks and opportunities.
• Provide analytics on user behaviors and market research to support more informed product decisions.

Minimum Requirements

• 3+ years of work experience in a data analytics role.
• Proficiency in querying and manipulating complex raw datasets for analysis using SQL, Python, and/or R.
• Experience with big data analytics platforms and tools such as Bigquery, Airflow, etc.
• Experience creating dashboards using Tableau (or similar) visualization tools.
• Ability to drive strategic discussions and convert strategy to action. Experience explaining technical concepts and analysis implications clearly to varied audiences and can translate business objectives into actionable analysis.
• Degree in Data Analytics, Economics, Computer Science, Operations Research, Math, or Statistics, with a quantitative focus.

Nice to Have

• Advanced degree with a quantitative focus (Data Analytics, Economics, Computer Science, Operations Research, Math, Statistics).
• Knowledge of logistics, warehousing, and supply chain is a plus.
• Knowledge of computer vision or machine learning.