Data Intern

Legend Biotech•Bridgewater, NJ

4d•Hybrid

About The Position

Legend Biotech is seeking a Data Intern to join its Information Technology team in Bridgewater, New Jersey. The intern will support the Data & Analytics team in collecting, organizing, analyzing, and visualizing data to enable business decision-making. The role offers hands-on experience with enterprise data, business intelligence tools, cloud data platforms, data quality, and documentation in a regulated life sciences environment. The intern will work with IT, business, and data teams on reports, dashboards, data processes, analytics, automation, and AI-enabled initiatives. It is suited to a student seeking practical experience in data analytics, data engineering, and business intelligence. The intern works under the guidance of the Data & Analytics team and may independently perform assigned analysis, prepare reports, document findings, and identify data quality issues. The role may recommend process improvements and highlight risks or issues, but architectural, compliance, financial, and strategic decisions require management approval. Applicants must be authorized to work in the United States. Legend Biotech participates in E-Verify; selected candidates must complete Form I-9 and have employment eligibility verified. The company provides equal employment opportunities without regard to protected characteristics. Employment is at-will.

Requirements

Currently pursuing a bachelor's or master's degree in Data Science, Computer Science, Information Systems, Statistics, Mathematics, Engineering, Bioinformatics, or Business Analytics.
Ability to break down problems and use data to develop insights.
Desire to learn new data, cloud, analytics, and AI technologies.
Attention to accuracy, completeness, consistency, and traceability of data.
Ability to summarize analysis and communicate findings clearly.
Ability to work effectively with technical teams and business stakeholders.
Ability to manage assigned tasks, meet deadlines, and raise issues when needed.
Willingness to learn unfamiliar systems, technologies, and business processes.
Basic knowledge of SQL and data analysis concepts.
Coursework, academic projects, or practical experience using Python or a similar programming language.
Authorized to work in the United States.

Nice To Haves

Familiarity with a data visualization tool such as Power BI, Tableau, or a similar platform.
Exposure to cloud data platforms or data engineering technologies.
Coursework or project experience involving machine learning, generative AI, or large language models.
Familiarity with data governance, data privacy, or regulated environments.
Interest in biotechnology, pharmaceuticals, healthcare, or life sciences.

Responsibilities

Collect, clean, transform, and analyze structured and unstructured data from multiple business systems.
Perform exploratory data analysis to identify trends, patterns, anomalies, and potential data quality issues.
Develop and enhance dashboards, reports, and visualizations using tools such as Microsoft Power BI.
Write SQL queries to retrieve, analyze, and validate data from databases and cloud data platforms.
Support data engineering activities, including data ingestion, transformation, validation, and reconciliation.
Help prepare analytics-ready datasets and support development of data and semantic models.
Support enterprise data platform initiatives using technologies such as Snowflake, Microsoft Azure, Microsoft Fabric, or similar cloud platforms.
Document data sources, transformations, lineage, metadata, and business rules.
Perform data quality checks and support resolution of data inconsistencies.
Work with business stakeholders to understand and document reporting and analytics requirements.
Assist with analytics, automation, and AI-enabled solutions where appropriate.
Participate in testing and validation of reports, dashboards, datasets, and data pipelines.
Prepare technical documentation, presentations, and analytical summaries.
Follow organizational requirements for data privacy, cybersecurity, data governance, and handling confidential information.
Perform other data and analytics-related activities as assigned.
Recommend process improvements and identify risks or issues, with management approval required for architectural, compliance, financial, or strategic decisions.