Label Insight’s core business model is extracting meaning from product packaging. This involves the processing of both semi-structured data such as Nutritional Fact Panels, Ingredient lists to unstructured natural language such as marketing claims, product descriptions and preparation instructions with a strong focus on text classification.
Assist with improving existing models that include, Image Classification, Optical Character Recognition (OCR), Natural Language Understanding (NLU)
Help in the definition and tuning of developed models in real-world production data processing pipeline
Work with engineering teams to ensure maximum business value from data science initiatives
Interact cross-functionally with a wide variety of people and teams
Perform data analysis on large, complex data sets
Provide guidance on data visualization on large, complex data sets
Use the latest technologies to solve business-critical problems
Knowledge with at least one statistical software (e.g., R, Python, Julia, MATLAB, pandas) and database languages (e.g., SQL).
Demonstrated skills in selecting the right statistical tools given a data analysis problem.
Demonstrated knowledge in one or more of the following Natural Language Understanding, Computer Vision, Machine Learning, Algorithmic Foundations of Optimization, Data Mining or Machine Intelligence (Artificial Intelligence).
Exposure to one or more of the latest industry technologies and processes (AWS, S3, SQL, Jupyter, SageMaker, Event Driven Systems, Version Control)
At the end of this internship you will be able to:
Gain experience working in a unique startup company environment with an emphasis on collaboration.
Work on production systems applying the latest approaches in both Data Science and Data Engineering to solve real-world data problems
Gain experience with tools, processes, and frameworks used to support a technology business built on large, complex data sets
Gain an in-depth knowledge of Customer Package Goods domain with a focus on nutritional science
- Transparency: We share information freely and concisely as a team
- Collaboration: We respect diversity and work toward the solution together
- Iteration and Innovation: We speak up early, are honest about our limits, and leverage failure as an asset
- Intellectual Honesty and Humility: We encourage open debate and favor the best ideas
- Accountability: We own the successes and failures of our team
- Quality Driven: We hold our work to the highest standards and embrace problems as opportunities
Does this sound like you? We'd love to talk to you!
Label Insight is an equal opportunity employer