Data Science Intern: GenAI & Econ Analytics

Cimgroup; Los Angeles (CA); On-site; USD 23,000 - 32,000; Full time

Job summary

CIM Group in Los Angeles, CA is offering a Data Science Intern position at the intersection of business, economics, and data science. You will contribute to real-world projects within the Enterprise Data Management team, support GenAI and LLM use cases, and work with a modern Databricks Lakehouse environment to analyze financial and operational data.

You will partner with ML engineers, data stewards, and platform teams to build models, validate results, and produce narratives and visualizations

Qualifications

• Pursuing a bachelor’s or master’s degree in Economics, Data Science, Mathematics, Statistics, Finance, or related quantitative field.
• Strong foundation in mathematics, statistics, and econometrics.
• Programming in Python (or R) with Pandas/NumPy/scikit-learn.
• Demonstrated quantitative ability via coursework, research, hackathons, or projects.
• Interest in generative AI and GenAI with a desire to learn modern models.

Responsibilities

• Analyze real datasets end-to-end, framing questions and surfacing insights to inform investment decisions.
• Translate quantitative findings into narratives, visuals, and recommendations for stakeholders.
• Support development and iteration of statistical, econometric, and ML models from feature engineering to validation.
• Prototype GenAI/LLM applications to make data exploration and action easier.
• Collaborate with MLOps, Platform Engineering, and Data Stewards to move prototypes toward production.

Skills

Python

Pandas

NumPy

Statistics

Data Visualization

Communication

Education

Bachelor's/master's degree

Quantitative field

Tools

Databricks

scikit-learn

SQL

Git

Job description

CIM Group in Los Angeles, CA is offering a Data Science Intern position at the intersection of business, economics, and data science. You will contribute to real-world projects within the Enterprise Data Management team, support GenAI and LLM use cases, and work with a modern Databricks Lakehouse environment to analyze financial and operational data.

You will partner with ML engineers, data stewards, and platform teams to build models, validate results, and produce narratives and visualizations