Data Scientist - NLP

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Apache Hadoop, Scala Programming, Machine learning techniques, Data science techniques, PyTorch, TensorFlow, MapReduce, R Programming

Job Description

Bose is about better sound, but better sound is just the beginning! We’re about inventing new technologies that truly benefit people and crafting a culture where innovation and collaboration are highly valued. Working at Bose, you’re encouraged to question conventional thinking in the steadfast quest to build products and experiences that change people's lives. Data science, ML, and analytics are a crucial part 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.

We are seeking a Data Scientist with experience delivering NLP driven solutions with a focus on deep learning frameworks and pre-trained language models. In this role, you will be responsible for crafting predictive models to analyze unstructured data like surveys, reviews, and other sources. You will apply your practical experience dealing with messy data, your deep understanding of ML and NLP fundamentals and algorithms, and your willingness to write code to explore problems and uncover patterns in data. The required technical and professional qualifications may come from a combination of professional, academic, research, consulting, pro bono, and personal projects.

Responsibilities include (but are not limited to):

• Engage with business partners and collaborators to understand their challenges and translate them into data science solutions. 
• Coordinate data science and data engineering resources to achieve business goals. 
• Lead, contribute, and provide thought leadership on the end-to-end development and deployment of predictive and prescriptive models for marketing, sales, finance, supply chain, and other business applications.
• Explore large datasets using modeling, analysis, and visualization techniques. 

• Apply Frequentist and Bayesian inference methodologies to experimental and observational data.
• Deliver presentations to senior business collaborators that tell a cohesive and logical story using data.

What's in it for you:

• Be a part of and work with a small, multidisciplinary, and agile team. 

• Build your career with people who want to solve problems, develop their expertise, and have fun together.
• Work on adding innovative capabilities to elite Bose business services.
• Excellent work-life balance and a continuous learning environment.
• Highly driven package as well as a comprehensive benefits program. 

Required qualifications:

• MA or MS in a quantitative field such as Computer Science, Statistics, Engineering, Information Science, etc. Alternatively, two years of Masters-level equivalent work experience plus a BA or BS in a quantitative field. 
• Expertise in advanced analytics, statistics, data science, or related areas.
• Excellent interpersonal, communication, and presentation skills.
• Experience collaborating with multiple collaborators on analytics, data science, ML, or NLP projects.
• Working knowledge of Git and GitHub.
• Experience contributing to at least three predictive models deployed into production.
• Three years of experience working with SQL, Python, and pandas/NumPy/SciPy.
• Two years of experience working with scikit-learn.
• One year of experience working with TensorFlow/PyTorch and pre-trained language models.
• Three years of experience in data analytics, business intelligence, etc.
• Two years of experience in data science, data engineering, etc.
• Two years of experience in NLP.
• Two years of experience creating dashboards and visualizations in a data visualization platform like PowerBI, Tableau, Spotfire, etc. 

Preferred qualifications:

• Two years of professional experience working in a client-facing consulting role. 

Bose is an equal opportunity employer that is committed to inclusion and diversity. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, genetic information, national origin, age, disability, veteran status, or any other legally protected characteristics.