Mirage is redefining short-form video with frontier AI research.
We’re building full-stack foundation models and products that are changing the future of this format and video creation, production and editing more broadly. Over 20 million creators and businesses use Mirage’s products to reach their full creative and commercial potential.
We are a rapidly growing team of ambitious, experienced, and devoted engineers, researchers, designers, marketers, and operators based in NYC. As an early member of our team, you’ll have an opportunity to have an outsized impact on our products and our company’s culture.

REQUIREMENTS:

• 5+ years as a data scientist or in a similar role with a focus on product analytics
• High proficiency in SQL and either Python or R for data manipulation, analysis, and modeling
• Expertise in statistical analysis, hypothesis testing, and experimental design for A/B testing and product experimentation
• In-depth knowledge of data visualization tools and techniques to effectively communicate insights and storytelling
• Strong analytical thinking and problem-solving skills, with the ability to translate complex data into actionable recommendations
• Strong written and verbal communication skills and the ability to partner with cross-functional teams to build a great business

ABOUT THE ROLE:

As a member of our Data Science staff, you’ll own end-to-end measurement by defining north-star metrics, architecting rigorous experiments, and converting insights into roadmap-shaping decisions. You’ll partner with Product, Design, and Engineering to elevate instrumentation and data quality and deliver quantified recommendations that improve activation, engagement, retention, and revenue.

Key Responsibilities:

• Lead analysis and exploration to uncover trends in product and user behavior and prioritize the highest leverage opportunities
• Design and evaluate rigorous A/B tests and set success criteria and power and guardrails and deliver clear post experiment readouts
• Collaborate with cross functional leaders to define core metrics and establish data driven goals for product experimentation
• Develop and maintain analytical models and reproducible pipelines that support full funnel analytics
• Apply statistical techniques to identify patterns and opportunities in large datasets and quantify expected impact and risk
• Create executive ready visualizations and dashboards that drive alignment and action among stakeholders
• Embed with designers and engineers to guide instrumentation and ensure data informed decisions throughout the product lifecycle
• Provide recommendations to improve user experience and conversion and overall product performance and track realized impact
• Stay current on industry trends and emerging technologies in analytics and introduce pragmatic improvements to tools and methods