Data Scientist (Atlanta, GA)
Are you passionate about applying data science to real business and customer needs? Would you like to use your data science and leadership skills to help our customers do more, feel more, and be more? At Bose, we aim to bring products into the world that people truly love, and we don’t stop until the details are just right. Data science, machine learning, 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 looking to bring in a bright and enthusiastic mid-level data scientist with a specialized focus on time series modeling within our Data and Analytics COE. The mission of this team is to develop world-class data science, machine learning, and statistical solutions to extract insights and enable data driven decisions that improve our business and enhance customer experiences. We achieve this by providing algorithmic and statistical expertise across the company to answer some of the most challenging decisions in areas such as price optimization, demand forecasting, drivers of customer loyalty, real-time personalization, and more.
- Engage with business partners and stakeholders to understand business problems and translate into data science solutions.
- Collaborate with data science, data engineering, and data governance resources to achieve business outcomes.
- Partner with other data scientists in the 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 statistical inference tools to experimental and observational data.
- Continually seek opportunities to enhance business processes through data-driven solutions.
- Communicate results, analyses, and methodologies to technical and non-technical stakeholders.
Education and Experience:
- Degree in Data Science, Machine Learning, Computer Science, Statistics, or a related field.
- Completed coursework related to Statistics, Computer Science, Machine Learning, and Data Science.
- Completed coursework related to Business/Management or Business/Customer Analytics preferred.
- 3-5 years of practical experience as a data scientist, from conceptualizing to building, deploying, and maintaining production-grade data science models.
- At least 1-2 years of experience specifically in developing and deploying time series models.
- Experience applying data science, AI/machine learning, and analytics techniques to business problems.
- Hands-on experience in constructing, deploying, and managing time series models in production.
- Familiarity with contemporary time series libraries such as, including Prophet, PyCaret, Darts, and others.
- Capacity to think strategically, crafting both tactical and long-term solutions in alignment with organizational requirements.
- Excellent communication, collaboration, and problem-solving skills.
- Strong programming background with experience in Python.
- Strong understanding of machine learning core concepts and techniques.
- Statistical inference (including frequentist and Bayesian) concepts and techniques preferred.
- Experience solving real-world problems with data at IoT scale using tools such as SQL, Spark, and Python is preferred.