Lead Data Scientist driving the development of personalization and recommendation systems at GoPay. Collaborating with Product and Engineering teams to deploy scalable ML pipelines.
Responsibilities
Drive the development of GoPay’s personalization and recommendation systems to deliver relevant offers, merchants, and experiences.
Define the technical direction for recommendation models.
Work closely with Product and Engineering to deploy scalable ML pipelines.
Lead experimentation to measure business impact.
Continuously improve models in production.
Mentor data scientists.
Align personalization efforts with GoTo’s broader roadmap.
Requirements
6–8 years of relevant experience in applied data science or machine learning roles.
Proficiency in Python, and familiarity with ML frameworks such as Scikit-learn, TensorFlow, or PyTorch.
Solid understanding of ML fundamentals including supervised learning, ranking, embeddings, and evaluation metrics.
Hands-on experience in recommender systems, personalization, search, or ranking models is strongly preferred.
Experience working with large-scale datasets using platforms such as Spark, MaxCompute (MC), or other distributed data environments.
Strong analytical and problem-solving skills, with the ability to translate complex data insights into actionable recommendations.
Good communication skills to engage with cross-functional partners and present results clearly.
Master’s or Ph.D. in a quantitative discipline (e.g., Computer Science, Statistics, Applied Mathematics, or related field) is a plus.
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