Data Engineer Intern

Summer 2027 Data Engineer Intern – Alternative Data

Location: New York, NY | Hybrid

Program Duration: Summer 2 Weeks) (30 hr per week commitment)

Looking for applicants anticipated to graduate between December 2027 & May 2028

Take the next step in your career now, scroll down to read the full role description and make your application.

About M Science

M Science is a data-driven research and analytics firm, uncovering new insights for leading financial institutions and corporations. We are revolutionizing research, discovering new data sets, and pioneering methodologies to provide actionable intelligence. Our research teams have decades of experience working with massive amounts of unstructured data in near real-time to discern critical insights that help clients make smarter, more informed decisions. We combine the best of finance, data, and technology to create a truly unique value proposition for hedge funds, asset managers, financial services firms, and major corporations.

The Opportunity

We are seeking a Data Engineer Intern to join our team for the summer. This internship is designed for students who are passionate about data, technology, and problem-solving. You will gain hands-on experience working with large datasets, building data pipelines, and supporting real-world research initiatives. Interns at M Science work alongside experienced data scientists and engineers to support impactful research used by hedge funds, asset managers, and other institutional clients.

Key Responsibilities

• Assist in building and maintaining scalable data pipelines and workflows.
• Support the design and optimization of data storage and retrieval systems.
• Work with cloud-based technologies (AWS, Databricks, Snowflake) to process structured and unstructured datasets.
• Help implement data quality checks, testing frameworks, and validation processes.
• Collaborate with engineers, analysts, and researchers to translate business questions into technical solutions.
• Explore and prototype new tools or methodologies to improve efficiency in data processing.

What You'll Learn

• Best practices in ETL/ELT development and pipeline orchestration.
• Working with big data tools like Spark, Databricks, and Airflow.
• Fundamentals of data governance, lineage, and quality assurance.
• Application of SQL and Python to solve real-world data problems.
• Exposure to financial services research and the use of alternative data in decision-making.

Preferred Qualifications

• Currently pursuing a Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, Statistics, or a related field anticipated to graduate between December 2027 and May 2028
• Experience with Python (data processing libraries such as Pandas, PySpark a plus).
• Knowledge of SQL and basic query optimization.
• Familiarity with cloud computing platforms (AWS, Azure, or GCP).
• Strong analytical and problem-solving skills.
• Curiosity, eagerness to learn, and ability to work both independently and in teams.

Nice-to-Have Skills

• Exposure to big data tools (Databricks, Spark).
• Familiarity with data modeling concepts (star schema, dimensional modeling).
• Experience with version control (Git) or CI/CD workflows.
• Interest in financial services, fintech, or alternative data research.

Why M Science?

• Gain hands-on experience in a fast-growing alternative data and analytics firm.
• Work directly with senior engineers and analysts on impactful projects.
• Hybrid work model offering both in-office collaboration and flexibility. xhyhwjd
• A culture that values learning, innovation, and curiosity.

Hourly Rate: Up to $45/hr USD