4+ years of experience in a Data Science, Data Analysis, or Data Visualization role. Hands-on experience with LLMs, RAG architectures, and prompt engineering. Strong proficiency in Python and ML/data science libraries. Applied knowledge of statistical data analysis, predictive modeling, classification, Time Series techniques, sampling methods, multivariate analysis, hypothesis testing, and drift analysis. Proficiency in SQL and experience with cloud data platforms (Snowflake, Spark, BigQuery, etc.) Expertise with data visualization tools (such as Tableau, d3, plotly, etc.) for data analysis and presentation.
Experience with Tableau Server, TabPy, and Extensions is a plus. Experience with Git and collaborative development workflows. Familiarity with deployment frameworks and tools (Docker, Kubernetes, FastAPI, or similar). Comfort with ambiguity. Ability to structure complex analysis through data analysis and strategy research. Proven ability to translate business problems into technical solutions and communicate findings to non-technical stakeholders.
Experience co-developing with data scientists and software engineers in production environments. Strong time management skills with the ability to collaborate across multiple teams. Able to balance competing priorities, long-term projects, and ad hoc requirements. Bachelor’s degree in Computer Science, Statistics, Mathematics, Engineering, Economics, Applied Mathematics, Machine Learning, or a related field.