Entry-Level NLP Data Scientist

THE ROLE

Bose is about better sound, but better sound is just the beginning. We are about inventing new technologies that truly benefit people and creating a culture where innovation and teamwork are highly valued. Working at Bose, you are encouraged to question conventional thinking in the relentless quest to create products and experiences that change people's lives. Data science, ML, and analytics are crucial parts of this mission. These capabilities fuel the creation of new and innovative products, help us to bring the right products to the right customers, and allow us to astonish customers with carefully crafted and personalized experiences. 

The Data and Analytics Center of Excellence is seeking an entry-level Data Scientist to help apply data-driven solutions to real-world business challenges. In this role, you will develop predictive models to analyze both structured and unstructured data, leveraging your knowledge of statistics, data science, and machine learning. You will write production-quality code to explore complex problems, identify patterns, and generate actionable insights. This position has a strong focus on natural language processing (NLP) and Generative AI, and familiarity with these areas is highly desirable.

Responsibilities include (but are not limited to): 

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. 

Required Qualifications:

Bachelor’s degree in a quantitative field such as Computer Science, Statistics, Applied Mathematics, Engineering, Information Science, or a related discipline.

0–2 years of professional experience in analytics, data science, machine learning, or a related field.

Proficiency in SQL and Python, including experience with libraries such as pandas and scikit-learn.

Experience building, evaluating, and interpreting classical machine learning models (e.g., Logistic Regression, Random Forests, Multi-layer Perceptron).

Foundational experience in natural language processing (NLP), including exposure to large language models (LLMs), transformer architectures (e.g., BERT, GPT, T5), semantic search, or text summarization.

Strong interpersonal, communication, and presentation skills, with the ability to explain technical concepts to diverse audiences.  

Preferred Qualifications:

Proven data science experience via an internship, work experience, competitions, etc.

Knowledge of deep learning basics.

Experience with Databricks and Snowflake.

Familiarity with LangChain, Hugging Face Transformers, Llama 3.x, OpenAI APIs, Pydantic, MLflow, and Streamlit. 

Working knowledge of Git and GitHub.