We believe data science is not about making complicated models, visualization, query, or writing code; it is about using data to create as much of an impact as possible on Kargo’s business. You will deal with ambiguous and complex problems. We expect you can guide the company in the right direction via insight or recommendation.
You will take full ownership of turning discoveries and ideas into machine learning models, while at the same time simplify and clearly communicate complex concepts to non technical persons. And the last bust most important is Identify the impact of data science solutions and create metrics to measure them.
For example Life as Data Scientist at Kargo, you have regular visits to the transporter, shipper, and warehouse to understand the ground truth and extract the parameters from customers’ brains on how they made pricing decisions into a statistics model. Then, you discuss with Product, Sales, and Biz stakeholders to build the MVP for standardized pricing recommendation. This is not a back office or remote working type; it is heavy on both on-field and office collaboration.
The fun part is that you will work directly with CTO to build the data scientist team's ground and prove that we can grow business by leveraging data. Due to the early stage development, you will own the responsibilities from data collection, storing, transforming, labeling, modeling, and hopefully optimizing with learning.
Requirements
- 3-5 years of experience in a combination of Data Science, Statistics, and Coding
- Fluency in Data-preprocessing using Python Programming and CSV/Excel/SQL
- Able to make sense of unstructured data (K-means, Unsupervised Learning, PCA & t-SNE)
- Knowledgeable in Regression and Prediction (Boostraping, Ensemble, Random Forest)
- Experience in bringing the model to production
- Proven stakeholder management skills in a previous company
- Fluent in English, both written and oral
- A Kaggle or Hugging Face profile or join one of the competition
- Experience in building ML or Deep Learning models in production (small-medium scale from scratch)
- Experience building standardized pricing models (based on the timeline, distribution, geolocation, etc.)
- Experience in Logistics
Kargo Technologies