We are seeking a Data Scientist to join our Data team, reporting to the Data Science Tech Lead and working side by side with the business, marketing, and engineering teams, following a philosophy 100% Agile.
You and the rest of the Data team will have the ownership to research, develop, test, maintain, and deploy systems which extract the full value from data in order to ask and answer questions, make decisions, and fuel data products, all to improve the experience for our customers, sellers and internal stakeholders.
Tasks and Responsibilities:
- Interface with stakeholders to understand and solve their data needs, to brainstorm and co-create new data products with them, to help them make data-driven decisions and use generative AI.
- Create, evaluate, & improve a diverse variety of data products including smart/optimization/personalization algorithms, AI agents, LLM applications, recommender systems, and predictive models.
- Develop these analytics, models, and algorithms from the initial idea to the implementation deployed in production, with a mind toward the final consumer/stakeholder, accuracy, scalability, and an iterative approach.
- Care for the standards and quality of your analyses, code, and implementation.
- Support your teammates by participating in data science brainstorming discussions, reviewing their code and results, and working collaboratively, especially during the POC/R&D phase.
What we are looking for:
- Minimum 2 years of experience as a Data Scientist, in a customer-centric company, preferably e-commerce, transactional marketplace, or e-health.
- Degree in Computer Science, Data Science, Engineering, Statistics or similar.
- Experience creating, evaluating, & improving Data Products using:
- Advanced Python: Libraries including pandas/polars, PyTorch, LangChain, etc; Deployed to production environments, using Kubernetes or other cloud-native deployment solutions
- Advanced SQL: Snowflake, Redshift, BigQuery or other data warehouse
- Domain knowledge: Marketing, business, finance, logistics, health, etc.
- Background skills: ML/LLMOps, data analysis/visualization/pre-processing, statistics, a/b testing, quantitative and qualitative analysis, cloud, etc.
- Past Data Engineering and/or Data Analysis experience (full-stack mindset) is a big plus.
Other Skills:
- Version control GIT
- Languages: Spanish and English (proficiency), German is a plus
- Experience in Agile methodologies
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