Senior Data Analyst

• Collaborate as a strategic partner with the Head of Engineering, Product Owner, and business stakeholders to analyze and evaluate current product and business processes, identifying data-driven opportunities for optimization and long-term improvement.
• Own end-to-end analytics workstreams: collect, interpret, and analyze data from multiple sources to support high-impact product and business decisions.
  Tackle ambiguous, open-ended data problems by asking the right questions, clarifying objectives, and uncovering insights that directly influence product direction and business strategy.
• Ensure data quality and integrity through rigorous filtering, cleaning, validation, and monitoring of reports and performance indicators to detect anomalies and inconsistencies.
• Build advanced dashboards, analytical models, and reporting solutions that drive decision-making, enable visibility, and improve performance across teams.
• Work directly with senior management to prioritize data needs, provide high-level recommendations, and support strategic, executive-level decision-making.
• Communicate insights with clarity and influence, translating complex analyses into business context for both technical and non-technical stakeholders.

Provide data-driven consultation to enhance product features, user experience, and operational processes, ensuring analytics plays a central role in shaping product and business outcomes.

Compensation & Benefits

• Competitive salary with 13th-month pay and performance bonus.
• Paid leave — vacation, sick leave, and maternity leave.
• Full social insurance coverage and premium healthcare benefits.

Build Your Career with Impact

• Be part of a mission-driven company that’s transforming human potential.
• Empower over 200,000+ coaches in more than 200 countries — including Olympic athletes, military trainers, rehab specialists, and celebrity coaches.
• Make a global impact while building a meaningful, purpose-driven career.
• Continuous training and mentoring.
• 1–2 performance reviews annually.

Work Environment

• English-speaking, international environment promoting open communication and collaboration.
• Work alongside world-class talent from companies like Apple, Meta, Uber, Patreon, and Nike, united by a shared passion for impact and excellence.
• International team for global career growth.
• State-of-the-art equipment provided.
• Beautiful working environment near Danang's city center (Dragon Bridge) and Hanoi office.

Health & Wellness

• PVI health insurance program and annual health check-ups.
• Active sports clubs (football, badminton, pickleball) and company retreats.
• A modern pantry designed for relaxation and social connection.
• Monthly wellness and learning workshops to recharge and grow.

• 5+ years of hands-on experience in data analysis, business intelligence, or a related quantitative field, with a proven track record of driving measurable impact.
• Exceptional analytical and critical-thinking skills, with the ability to collect, organize, analyze, and interpret large and complex datasets with a high level of accuracy and attention to detail.
• Strong product sense, capable of understanding user behavior, identifying business opportunities, and shaping product direction through data-driven insights.
• Advanced proficiency in SQL and strong experience working with modern databases (e.g., MongoDB), along with a solid understanding of data modeling, schema design, and performance optimization.
• Excellent communication and data storytelling skills, able to translate complex analyses into clear, actionable insights for cross-functional stakeholders and senior leadership.
• Demonstrated ability to work with sensitive or confidential information with integrity and discretion.
• Strong command of English (verbal and written), with the ability to present analytical findings and strategic recommendations confidently.

Nice to have:

• Experience with Stripe Sigma or other payment analytics tools.
• Knowledge of data architecture concepts such as Data Lake, Data Warehouse, Data Mart, or Data Mesh.
• Experience with BI tools or data visualization platforms (e.g., Looker, Power BI, Tableau).
• Familiarity with experimentation frameworks (A/B testing) or product analytics tools.