About us:
At Cognira, we strongly believe that people are the biggest asset of our company. Our hand-picked team consists of passionate, collaborative, and forward-thinking individuals from all over the globe. We are passionate about making science easy and accessible to retailers, helping them get more value from people, data, and systems. We bring together expertise in retail, science, and scalable technologies to automate and enhance the quality of decision-making through software and consulting services.
For the last three years in a row, Cognira has been recognized as one of the fastest-growing companies in North America. We are proud to have a growing team of domain experts and data scientists, as well as a culture that fosters strong and long-lasting relationships with our clients.
Our values:
Important: Please submit your resume in English only.
About this internship:
You will be part of a high-growth software company. Our program is designed so interns can grow their skill sets, do meaningful work, and have a lot of fun along the way!
We're looking for highly talented & motivated interns to join our Data Science team and nail one of the following projects:
Project 1: Explainable AI (XAI) in Demand Forecasting.
Making machine learning models more interpretable and trustworthy for demand forecasting by applying explainable AI techniques. Use methods like SHAP (Shapley Additive Explanations) or LIME (Local Interpretable Model-agnostic Explanations) to explain predictions made by simple and complex models (e.g., linear regression vs deep learning) to non-technical stakeholders.
Project 2: Integrating Semantic Similarity for Enhanced SKU Grouping and Detection
Past forecast assessments revealed cases where products appear suited for grouping under a new level, termed ‘super_SKUs.’ The current grouping method relies on time series patterns, but incorporating semantic understanding could improve accuracy and add valuable business insight.
This internship will explore adding semantic similarity metrics directly to the SKU detection process or as a post-processing validation step for ‘super_SKUs.’ This approach will leverage a language model, such as product embeddings from transactions, or involve fine-tuning an existing LLM architecture.
About you:
Important: Please submit your resume in English only.
What you'll enjoy here: It's not just an internship; we've got some great added value for you too. Here's what you'll enjoy:
[ Important: Please send us your resume in English only ]