Senior Data Scientist
Label Insight is the industry leader in powering product attribute-driven growth across the consumer-packaged goods ecosystem. Their patented technology harnesses data science and machine learning to create best-in-class product attribute data with more than 22,000 high-order attributes per product.
Covering more than 80 percent of top selling food, pet, and personal care items in the U.S., Label Insight enables companies to unlock new growth opportunities and power digital innovation across their business while empowering consumers to make more informed purchasing decisions with better product transparency.
The company, with locations in Chicago and St. Louis, supports industry leading clients including Unilever, ConAgra, Pepsi, Walmart, Target, Albertsons, Petco, Meijer, Dole and numerous other CPG brands and retailers.
About the role:
As a Data Scientist, you will evaluate and improve LI’s products. You will collaborate with a multi-disciplinary team of engineers on a wide range of problems. This position will developing deep learning models to extract information from text and images.
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. We’re seeking a Data Scientist focused on computational linguistics/natural language processing who can leverage their creativity and experience to build connections and unearth hidden value in existing and new data sources. You will collaborate closely with technologists and business stakeholders on the transition of your research into high value business applications.
- MS degree in a quantitative discipline (e.g., statistics, operations research, bioinformatics, economics, computational biology, computer science, mathematics, physics, electrical engineering, industrial engineering).
- 2 years of relevant work experience in data analysis or related field. (e.g., as a statistician / data scientist / computational biologist / bioinformatician)
- Experience with 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 effective written and verbal communication skills.
- Demonstrated willingness to both teach others and learn new techniques.
- 4 years of relevant work experience (e.g., as a statistician / computational biologist / bioinformatician / data scientist), including deep expertise and experience with statistical data analysis such as linear models, multivariate analysis, stochastic models, sampling methods.
- Applied experience with machine learning on large datasets.
- Experience in Natural Language Understanding, Computer Vision, Machine Learning, Algorithmic Foundations of Optimization, Data Mining or Machine Intelligence (Artificial Intelligence).
- Contribution to research communities and/or efforts, including publishing papers at conferences such as NIPS, ICML, ACL, CVPR, etc.
- Any experience with nutritional science and the product marketing domain would be highly advantageous
- Knowledge of graph database technologies, such as Neo4J or some experience with data classification, taxonomy building, and/or metadata schemas
- Interact cross-functionally with a wide variety of people and teams. Work closely with engineers to identify opportunities for, design, and assess improvements to LI products.
- Make recommendations around existing models that include, Image Classification, Optical Character Recognition (OCR), Natural Language Understanding (NLU).
- Work with large, complex data sets. Solve difficult, non-routine analysis problems, applying advanced analytical methods as needed. Conduct end-to-end analysis that includes data gathering and requirements specification, processing, analysis, ongoing deliverables, and presentations.
- Work with ontologies, taxonomies and vocabularies within a nutritional science context
- 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
- Flexible paid vacation
- Flexible work hours
- Kitchen stocked with snacks, drinks, a kegerator and more!
- Casual, dog-friendly, open-layout workspace
- Company subsidized Health Insurance, and 401(k) and commuter benefits
- Competitive salary and stock options
- Catered team lunches every other week
- Regular team events and happy hours
- Maternity/Paternity Leave
Does this sound like you? We'd love to talk to you!
Label Insight is an Equal Opportunity Employer