Cynamics is the only sample-based, next-generation network detection and response for threat prediction and visibility at scale. It's probe-less and agent-free and uses just 1% of network traffic to get 100% visibility. Not only cutting edge technology, Cynamics developed a fresh Product Led Growth business model. As the Growth Analyst, you will be a crucial part of this unique model: you will be responsible for leading the continuous growth and improvement of Cynamics success.
We are seeking a talented professional who thrives at the intersection of Product Analytics and Growth Marketing. The ideal candidate will have a strong technical, analytical and a great business sense.
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Identify growth opportunities and constantly work toward improving our adoption, engagement and ability to monetize.
Partner with different stakeholders (product managers, designers, and engineers) to execute on Cynamics product based on what you identified as key factors to accelerate growth and adoption
Understand the funnels, user behavior and the KPIs that move the needle the most for the business.
Apply your expertise in quantitative analysis, data mining, data visualization and the presentation of data to see beyond the numbers in a way that is clear, concise and insightful.
Highly independent individual who is full of curiosity and creativity about new opportunities to grow the products, and execute these ideas on his own.
2+ years experience in making analytical, data-driven decisions and communicating the results to key stakeholders.
2+ years experience manipulating data sets using SQL and/or other programming languages.
2+ years experience working collaboratively with product and marketing team members
Experience with product optimization work i.e. funnel/website optimization.
Experience working with Visualization and Analytics tools such as Google Analytics (preferred), Amplitude, Salesforce, etc.
Familiarity with Product Led Growth methodologies such as A/B testing techniques, experiementions, growth funnels, etc.
Bachelor’s Degree in a data related field - Industrial Engineering, Statistics, Economics, Math, Computer Science, Business etc.