Payment Optimization - APM Lead
Team: Customer Success
Location: Montevideo, Buenos Aires, Sao Paulo
Commitment: Full Time
Workplace Type: hybrid
We are looking for a strategic and experienced Data Analyst Lead who is eager to drive significant impact in our Product and Payments domain. If you have a passion for solving complex, high-stakes business problems, leading data analysis initiatives, and being the key source of strategic insights for Product teams, we encourage you to apply!
In this lead role, you'll be responsible for spearheading product-focused data analytics across different payment flows. You’ll be designing and executing a scalable, continuous optimization strategy to maximize payment conversion rates and drive product success.
What will I be doing?
- Deeply understand how our customers such as Amazon, Spotify, Booking, or Uber are using Dlocal to process payments, specifically focusing on product performance and user experience data.
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Act as a leader during the ramp-up of new customers, by conducting advanced analysis of transaction information and proactively identifying key product and process improvements. This involves examining millions of data points, recognizing complex failure patterns, and translating findings into product requirements.
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Design, coordinate, and lead A/B tests and experimentation to continuously improve key performance indicators (KPIs) and validate product hypotheses.
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Work closely and be the strategic data partner for our Product, Machine Learning, Operations, APM vertical, and Customer Success teams, providing the core insights needed to develop new, high-impact product solutions focused on APMs.
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Mentor and guide analysts on best practices for data extraction, analysis, and visualization.
What skills do I need?
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Analytically driven with extensive experience manipulating large data sets in SQL or equivalent, and translating complex data into clear, actionable, product-focused insights.
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2+ years of experience in product and payments analytics, including experience in a leadership, senior, or mentoring capacity.
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Extensive experience and passion for defining metrics and creating compelling dashboard visualizations to track product health and business impact.
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Highly skilled at writing optimized SQL to query relational databases; strong proficiency in R or Python for advanced statistical analysis is a plus.
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Strong communication and presentation skills, with the ability to influence technical and non-technical stakeholders (English is a must).
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Degree in a quantitative field (e.g., Statistics, Economics, Math, Sciences, Engineering, Data Science)
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