Bose is looking for students to join their Co-Op Program to apply data science knowledge to real-world challenges, specifically focusing on creating predictive models for analyzing structured and unstructured data, with an emphasis on NLP and GenAI, to fuel the creation of new and innovative products, bring the right products to the right customers, and astonish customers with carefully crafted and personalized experiences.
Requirements
- Two years of experience with SQL , Python , pandas, and scikit-learn.
- Experience fitting and evaluating classical ML models (Logistic Regression, Random Forests, Multi-layer Perceptron, etc.) .
- Prior NLP experience, including working with LLMs, fine-tuning transformer architectures (e.g., BERT, GPT, T5), semantic search, or text summarization.
- Knowledge of deep learning basics.
- Experience with Databricks and Snowflake.
- Familiarity wit h LangChain , Hugging Face Transformers, Llama 3.x, OpenAI APIs , Pydantic , MLflow , and Streamlit .
- Working knowledge of Git and GitHub.
Responsibilities
- Creating predictive models to analyze structured and unstructured data.
- Apply your knowledge of statistics, data science, and ML and your willingness to write functional code to explore problems and uncover patterns in data.
- Engage with business partners and stakeholders to understand their challenges and opportunities.
- Explore large datasets using modeling, analysis, and visualization techniques. Transform the results into insights and recommendations.
- Contribute to the end-to-end development of predictive and prescriptive models for marketing, sales, finance, supply chain, and other business applications.
- Design, build, and optimize workflows to streamline and automate the processing and delivery of data.
- Develop and maintain applications that deliver unique, insightful capabilities to empower end users through interactive and intuitive interfaces.
Other
- Currently enrolled in a bachelor's or master's degree program in a quantitative field such as Computer Science, Statistics, Applied Mathematics, Engineering, Information Science, etc.
- Good interpersonal, communication, and presentation skills.
- Developing expertise in analytics, BI, statistics, data science, or a related area.
- Proven data science experience via an internship, work experience, competitions, etc.
- Timeframe - January-June 2026
