Experience Required:

Bachelors or master's or PhD degree in quantitative discipline: Computer Science, Engineering, Data Science, Math, Statistics or related mathematically intensive fields such as Experimental Physics or Chemical Engineering
4+ years of industry experience in applying data science and modeling methodologies: regression model, survival model, ensemble modeling, NLP, recommendation algorithm, clustering, deep learning algorithm, experimental design (Multivariate/A-B testing) and nonparametric Bayesian modeling etc.
Experience with any of the following business analytics practices is preferred:
Supply chain analytics, including inventory optimization
Time series forecasting for large-scale demand forecasting
Ecommerce fulfillment operations, pick path optimization
4+ years of experience and proficiency in SQL, Python and/or Spark-ML
4+ years of SQL development skills writing queries, transforming data, mining structured and unstructured data.
2+ years of hands-on experience in building data science solutions and production-ready systems on big data platforms such as Snowflake, Spark, Hadoop
Ability to write production-level code in Python
Experience with Snowflake, Azure Databricks is a strong plus
Skills Required:

Statistical and Experimental Modeling (regression modeling, survival modeling, experimental design multivariate/A-B testing)
ML and AI (deep learning algorithms, NLP, nonparametric Bayesian modeling, ensemble modeling, recommendation algorithms, clustering)
Mathematical and Applied Optimization (operations research, linear optimization, non-linear optimization, numerical search)
SQL, Python
Skills Preferred:

Big Data and Tools (Spark-ML, Snowflake, Spark, Hadoop, Big Query)
Production-level Python coding
Data Engineering
AI Methodologies (GenAI, Agentic AI)

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