About the job
About ARQ
ARQ stands at the forefront of fintech innovation, rapidly establishing itself as a global leader. Our goal is to revolutionize the way individuals engage with their finances across borders, creating a seamless infrastructure for value transfer. As we embark on this exciting journey, each new team member plays a pivotal role in shaping our product, culture, and overall growth. If you are driven by significant challenges, aspire to make a global impact, and wish to thrive in a high-caliber team, ARQ is your ideal destination.
Position Overview
We seek a highly analytical and strategic Growth Analytics Manager to become a vital part of our Growth team. This role is crucial, with ownership over our growth data management, budgeting, and financial planning across our four primary markets.
Your expertise will be essential in converting raw data into strategic insights. Collaborating closely with the Head of Growth and our founders, you will drive business performance enhancements. If you possess a passion for merging intricate data analysis with a profound comprehension of consumer behavior, we are eager to connect with you.
Key Responsibilities
- Act as the analytical backbone for our Growth leadership team by presenting insights and strategic recommendations that directly impact budgeting, prioritization of roadmaps, and overall business strategy.
- Establish, track, and report on key performance indicators (KPIs) throughout the user journey (AARRR: Acquisition, Activation, Retention, Referral, Revenue).
- Perform complex analyses (e.g., cohort analysis, A/B tests, attribution modeling, lifetime value forecasting) to pinpoint growth optimization opportunities and analyze shifts in user behavior.
- Design, execute, and evaluate controlled experiments, delivering clear, statistically significant recommendations to product and marketing teams.
Qualifications
- A minimum of 4 years of professional experience in an analytical capacity.
- Preferred background from top consulting firms such as McKinsey, BCG, or Bain.
- Advanced proficiency in SQL for effective data querying, transformation, and analysis.
- Extensive experience with contemporary data visualization tools (e.g., Tableau, Looker, Power BI).
- Strong ability to utilize statistical tools or programming languages for data analysis (e.g., Python/R is a significant advantage).
- Thorough understanding of statistical significance and the execution of related methodologies.

