Processing and analyzing large volumes of data.
Building predictive models with advanced machine learning algorithms such as Neural Networks, Decision Trees, Boosting/Ensemble methods, Clustering, etc.
Implementing data quality checks to ensure that all reporting and modeling is using correctly sourced data.
Interacting with business teams from the data analysis stage to the final report presentation.
Assisting Product Managers as needed to define and refine business use cases.
Writing coherent reports and making presentations on high-end analytical projects.
Communicating verbally and in writing with peer technical team members as well as business leaders.
Assist in building or integrating Generative AI–powered features, such as intelligent assistants, automation workflows, or recommendation systems.
Gain exposure to agentic frameworks and patterns (e.g., tool-using agents, multi-step reasoning, orchestration of AI agents).

Experience in Machine Learning, Scripting, and Statistical & Reporting tools (Python, R, SQL, etc.)
Knowledge of at least some supervised and unsupervised modeling techniques such as Logistic/Linear Regression, SVMs, Neural Networks / Deep Networks, Boosting/Ensemble methods, Decision Trees, Clustering, etc.
Awareness of Generative AI concepts, including large language models (LLMs), prompt engineering, or AI-assisted development tools.
Willingness to extend beyond core data science work to perform -data wrangling, data prep and data transfers, data quality checks, deployment, monitoring
Ability to communicate clearly across data science team members
Experience with SQL and relational databases
Experience with unstructured and semi-structured data sources and requisite processing tools.

Data Science Intern

Key skills