About Fuze

Fuze is transforming the way businesses communicate. We seamlessly unify voice, video, and collaboration services on a single, cloud-based platform. And we provide intelligent apps that empower workforces anytime, anywhere, across any device. Headquartered in Boston, MA, with offices and customers worldwide, Fuze is a fast-growing, pre-IPO company that is building the communications platform for the modern, mobile business.

Engineering at Fuze

From business-critical services that can handle billions of voice, video, and messaging interactions per day, to consumer-inspired apps across all device types, we have no shortage of users, data, challenges and opportunities.

But it's no fun tackling big problems without a strong team and the right environment, and at Fuze we prefer to have fun. Engineering is built around a core of successful startup and software veterans -- we gravitate towards other self-driven, innovative, and productive people. Work is fast-paced, product-focused, and process-light. With offices in Boston, San Francisco, Seattle, New York, Ottawa, and Portugal we are a dynamic, globally distributed group that embodies the typical Fuze customer. And we have awesome benefits and a healthy sense of balance. At Fuze, we take joy in our work, take pride in our team, and take care of our people.

Data Scientist

Fuze is looking for an experienced data scientist to kickstart our data science & machine learning efforts. You will be engaged in the entire data science lifecycle, from problem formulation to data wrangling to building models to visualizing results. This is a new team and an opportunity to have a huge impact.

Qualifications:

• MS in Mathematics, Statistics, Economics or related quantitative field.
• You are comfortable using Python to collect, analyze, manage and report data required
• You have worked with multiple DB platforms such as MongoDB & PostgreSQL
• You are proficient with data science / machine learning tools including text analytics, topic modeling, sentiment analysis, classification, supervised and unsupervised learning methods, and static network models
• You can produce data visualizations that effectively communicate your results

• You must have excellent technical and non-technical communication skills, and experience working in small startup environments