- Experience
- 10+ yrs
- Salary
- USD 360,000 – USD 410,000 / year
- Openings
- 1
- Posted
- 5 గంటలు క్రితం
- Work mode
- Work from home
- Resume
- Required to apply
Job description
About MoonPay
MoonPay is a fast-paced, high-expectations company building the infrastructure for moving value online. The firm operates globally with licenses and regulations across the US, UK, EU, Canada, and Australia, serving over 30 million customers and integrating with more than 500 ecosystem partners. The company emphasizes AI integration in daily work to improve efficiency, focusing on outcome-driven performance and real ownership among team members.
Role Overview
As the Director of Data & Analytics, you will lead the Product Data & Analytics function under the CTO for Ramps & Platform. This role entails building and scaling a diverse team that includes Data Scientists, Analytics Engineers, and Data Analysts. Your responsibility is to establish the team’s operational framework and methodologies, making data-driven insights central to the company’s product development processes.
Responsibilities
- Lead the strategic direction, roadmapping, and operating model for Product Data & Analytics.
- Recruit, build, and guide multidisciplinary teams involving Data Science, Analytics Engineering, and Data Analysis.
- Develop organizational structure, leveling, and career progression to support scaling.
- Implement standardized product metrics, experimental design, and analytics frameworks replacing ad hoc reports with reliable data products.
- Collaborate closely with Product and Engineering leaders to integrate analytics and experimentation into the product lifecycle.
- Define technical standards for data modeling, experimentation methods, dashboarding, and reporting.
- Represent analytics requirements in cross-functional planning with various departments including Finance and Compliance.
- Mentor team leadership and cultivate future managers within the analytics group.
- Report key performance indicators related to team growth and analytics impact to senior executives.
Candidate Profile
- At least 10 years in data science, analytics, or related fields with significant leadership experience.
- Proven capability in founding or scaling a data/analytics function during rapid expansion.
- Strong partnership skills with Product and Engineering to embed data-driven decision-making.
- Technical knowledge sufficient to oversee data modeling and experimental approaches effectively.
- Excellent communication skills for diverse stakeholders, including executives and engineers.
- Experience in fintech, payments, or cryptocurrency is highly advantageous.
- Passion for the crypto and Web3 space and adaptability to a dynamic environment.
Compensation
Salary range: $360,000 to $410,000 USD annually.
Benefits and Perks
- Competitive salary complemented by an equity ownership plan.
- Performance-based equity bonuses rewarding major contributions.
- Biannual 'Moonshot' awards supporting exceptional impact, granting significant equity.
- Employer pension contributions starting immediately.
- Employee referral incentive offering $10,000 in USDC for successful recruitment.
- Flexible time off policies encouraging work-life balance.
- Birthday leave and enhanced parental leave options.
- Remote-first working options or access to physical locations.
- Commuter benefits for office attendance.
- Private healthcare coverage for employees and families.
- Wellness membership access to fitness and mental health resources.
- Unlimited enterprise AI tool access including Claude, ChatGPT, and Gemini.
- Meal credits for days spent at the office.
- Allowances for home office setup and remote work utilities.
- Monthly product budget and free crypto transactions.
- Annual $1,000 training budget to support ongoing learning.
- Structured development programs with mentorship and growth opportunities.
- Regular remote company offsites and in-person events.
- Tax-efficient bike and electric vehicle schemes in select regions.
Additional Information
Artificial intelligence aids the hiring process through resume analysis and identifying inconsistencies, but all final hiring decisions are made by humans. Inquiries about data processing during recruitment can be addressed upon request.