Business Analyst

October 18

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Vonage

WebsiteLinkedInAll Job Openings

UCaaS • CPaaS • CCaaS • Cloud Communications • Unified Communications

1001 - 5000

💰 $225M Post-IPO Debt on 2014-08

Description

• Support the technical execution of our monitoring needs, data analytics, testing, and automation. • Build, Maintain and Improve alerts on identified fields of each function of our team, to better Monitor and support our products. • Assist the Fraud team in Telecom Fraud and Compliance by developing new alerts and algorithms to identify fraudulent activity within the Vonage Network. • Liaise with our Data and Core teams to identify ways of improving the Data consumption for our projects and framework. • Work through a variety of technical challenges that will require creativity and close collaboration across internal functions.

Requirements

• 3-5 years of experience in Data Analysis and/or Analytics. • Skilled in reporting and data visualization software (Tableau BI or similar) • Exposure in Elasticsearch and its’ modules/extensions/language (Kibana, X-Pack, lucene query language) • Experience with Python. • Experience with SQL. • Experience with version control systems like Git • Creative and keen to learn new technologies • Self-starter who is also comfortable working individually as well as part of a team. • Inquisitive mindset, with a strong eye for detail. • Comfortable in planning, leading, and delivering complex data solutions to improve performance and to deliver improved alerts. • Have a strong quantitative analytical background and be able to draw out key information from large datasets. • Excellent communication skills, able to explain data concepts to non-technical audiences. • Project management skills with experience of working collaboratively with colleagues across large organizations. • Understanding of the b2b cloud communications industry, including but not limited to WebRTC, A2P messaging (Kafka), or VoIP. • Experience / Familiarity in Telecom Fraud - SMS and Voice • Experience in writing ETL/ELTs • Experience with Machine Learning libraries • Computer Science degree preferred but not required.