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Data Scientist – Product Analytics
Position Overview
We are seeking a Data Scientist with a focus on product analytics to design and implement data-driven solutions that influence strategic business decisions. This role involves applying predictive modeling, statistical analysis, and machine learning to uncover insights that directly improve product adoption, customer engagement, and business performance.
Why This Role Matters
In a world where commerce and payments systems are becoming increasingly complex, data science is essential for understanding user behavior and guiding product strategy. As a Product Analytics Data Scientist, your work will enable teams to make informed decisions, enhance customer experience, and drive measurable business outcomes.
About the Role
You will collaborate with engineers, product managers, and business leaders to design experiments, build data products, and present insights that shape future strategy. Your role requires balancing hands-on technical analysis with the ability to communicate complex findings to both technical and executive audiences.
Key Responsibilities
- Conduct ad-hoc analyses to evaluate initiatives, measure business impact, and uncover optimization opportunities.
- Partner with cross-functional teams to develop data requirements and establish critical product metrics.
- Design, deploy, and analyze experiments to improve business performance and customer outcomes.
- Apply machine learning algorithms such as regression, classification, and clustering to real-world product challenges.
- Explore emerging technologies, including generative AI, to create new business value.
- Advocate for responsible data collection, governance, and secure access practices.
Minimum Qualifications
- 3+ years of experience as a Data Scientist or Analyst in commerce, payments, product, or technology environments.
- Strong proficiency with SQL and distributed systems (e.g., Hadoop).
- Hands-on experience implementing pipelines in Python or Scala.
- Understanding of machine learning techniques such as classification, regression, clustering, and anomaly detection.
- Ability to extract business insights from large data sets and present findings clearly.
Preferred Qualifications
- Bachelor’s degree in a quantitative field (Computer Science, Statistics, Economics, Engineering, etc.) or equivalent experience.
- Advanced degree in Applied Econometrics, Machine Learning, Statistics, or related field.
- Experience in large-scale e-commerce environments.
- Strong knowledge of ML algorithms and prior AI development experience.
