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Description and Requirements
The Opportunity
When you join MetLife's Global Data & Analytics team, you'll collaborate with talented peers in cross-functional teams to solve business problems using data-driven approaches while expanding your skills in impactful ways. Ready to push boundaries and set new industry standards? Join us and help drive the future of technology forward.
We are seeking a Master's‑level Data Science Intern to join our Enterprise AI & Data Science team. This internship is designed for graduate students who want hands‑on experience applying advanced analytics, statistical modeling, and machine learning to real business problems. Interns will work on meaningful projects, collaborate with experienced data scientists and cross‑functional partners, and contribute insights that inform decision‑making.
Intern projects are varied and align to business needs.
What You Will Do (Key Responsibilities)
• Develop and evaluate statistical and machine learning models to address business use cases such as customer behavior, pricing, risk, underwriting, fraud, or operational efficiency
• Perform feature engineering, data exploration, and model validation using enterprise datasets
• Build and test data science prototypes or proof‑of‑concepts that demonstrate business value and technical feasibility
• Support model performance analysis, documentation, and governance in alignment with MetLife standards
• Communicate model insights, assumptions, and limitations clearly to technical and business stakeholders
What You Will Need to Succeed (Required Qualifications)
• Enrolled in a master's program in Data Science, Statistics, Computer Science, Applied Mathematics, or a related quantitative field
• Strong programming skills in Python for data science (e.g., pandas, numpy, scikit‑learn)
• Solid foundation in statistics, probability, and machine learning concepts
• Experience working with messy, real‑world datasets and translating them into model‑ready inputs
• Ability to explain modeling approaches and results clearly to non‑technical audiences
Preferred Qualifications
• Exposure to cloud‑based data science platforms (e.g., Azure, Databricks)
• Experience with model evaluation, experimentation, or time‑series methods
• Experience translating data and AI insights into impactful stories for technical and business audiences
• Familiarity with responsible AI, model governance, or risk considerations
• Experience collaborating with engineers or working in agile, cross‑functional teams
Location Expectation: This is a hybrid role requiring a minimum of 3 days per week in office.
The expected salary range for this position is 38-40/Hour.
About MetLife
Recognized on Fortune magazine's list of the "World's Most Admired Companies", Fortune World's 25 Best Workplaces™, as well as the Fortune 100 Best Companies to Work For®, MetLife, through its subsidiaries and affiliates, is one of the world's leading financial services companies; providing insurance, annuities, employee benefits and asset management to individual and institutional customers. With operations in more than 40 markets, we hold leading positions in the United States, Latin America, Asia, Europe, and the Middle East.
Our purpose is simple - to help our colleagues, customers, communities, and the world at large create a more confident future. United by purpose and guided by our core values - Win Together, Do the Right Thing, Deliver Impact Over Activity, and Think Ahead - we're inspired to transform the next century in financial services. At MetLife, it's #AllTogetherPossible . Join us!
MetLife is an Equal Opportunity Employer. All employment decisions are made without regards to race, color, national origin, religion, creed, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity or expression, age, disability, marital or domestic/civil partnership status, genetic information, citizenship status (although applicants and employees must be legally authorized to work in the United States), uniformed service member or veteran status, or any other characteristic protected by applicable federal, state, or local law ("protected characteristics").
If you need an accommodation due to a disability, please email us at [email protected]. This information will be held in confidence and used only to determine an appropriate accommodation for the application process.
MetLife maintains a drug-free workplace.
38-40
#BI-Hybrid
The Opportunity
When you join MetLife's Global Data & Analytics team, you'll collaborate with talented peers in cross-functional teams to solve business problems using data-driven approaches while expanding your skills in impactful ways. Ready to push boundaries and set new industry standards? Join us and help drive the future of technology forward.
We are seeking a Master's‑level Data Science Intern to join our Enterprise AI & Data Science team. This internship is designed for graduate students who want hands‑on experience applying advanced analytics, statistical modeling, and machine learning to real business problems. Interns will work on meaningful projects, collaborate with experienced data scientists and cross‑functional partners, and contribute insights that inform decision‑making.
Intern projects are varied and align to business needs.
What You Will Do (Key Responsibilities)
• Develop and evaluate statistical and machine learning models to address business use cases such as customer behavior, pricing, risk, underwriting, fraud, or operational efficiency
• Perform feature engineering, data exploration, and model validation using enterprise datasets
• Build and test data science prototypes or proof‑of‑concepts that demonstrate business value and technical feasibility
• Support model performance analysis, documentation, and governance in alignment with MetLife standards
• Communicate model insights, assumptions, and limitations clearly to technical and business stakeholders
What You Will Need to Succeed (Required Qualifications)
• Enrolled in a master's program in Data Science, Statistics, Computer Science, Applied Mathematics, or a related quantitative field
• Strong programming skills in Python for data science (e.g., pandas, numpy, scikit‑learn)
• Solid foundation in statistics, probability, and machine learning concepts
• Experience working with messy, real‑world datasets and translating them into model‑ready inputs
• Ability to explain modeling approaches and results clearly to non‑technical audiences
Preferred Qualifications
• Exposure to cloud‑based data science platforms (e.g., Azure, Databricks)
• Experience with model evaluation, experimentation, or time‑series methods
• Experience translating data and AI insights into impactful stories for technical and business audiences
• Familiarity with responsible AI, model governance, or risk considerations
• Experience collaborating with engineers or working in agile, cross‑functional teams
Location Expectation: This is a hybrid role requiring a minimum of 3 days per week in office.
The expected salary range for this position is 38-40/Hour.
About MetLife
Recognized on Fortune magazine's list of the "World's Most Admired Companies", Fortune World's 25 Best Workplaces™, as well as the Fortune 100 Best Companies to Work For®, MetLife, through its subsidiaries and affiliates, is one of the world's leading financial services companies; providing insurance, annuities, employee benefits and asset management to individual and institutional customers. With operations in more than 40 markets, we hold leading positions in the United States, Latin America, Asia, Europe, and the Middle East.
Our purpose is simple - to help our colleagues, customers, communities, and the world at large create a more confident future. United by purpose and guided by our core values - Win Together, Do the Right Thing, Deliver Impact Over Activity, and Think Ahead - we're inspired to transform the next century in financial services. At MetLife, it's #AllTogetherPossible . Join us!
MetLife is an Equal Opportunity Employer. All employment decisions are made without regards to race, color, national origin, religion, creed, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity or expression, age, disability, marital or domestic/civil partnership status, genetic information, citizenship status (although applicants and employees must be legally authorized to work in the United States), uniformed service member or veteran status, or any other characteristic protected by applicable federal, state, or local law ("protected characteristics").
If you need an accommodation due to a disability, please email us at [email protected]. This information will be held in confidence and used only to determine an appropriate accommodation for the application process.
MetLife maintains a drug-free workplace.
38-40
#BI-Hybrid
MetLife New York, New York, USA Office
MetLife New York City, NY Office
200 Park Ave, New York, NY, United States, 10166
MetLife Bridgewater, New Jersey, USA Office
MetLife Bridgewater, NJ Office
501 Route 22, Bridgewater, NJ, United States, 08807
MetLife Whippany, New Jersey, USA Office
MetLife Whippany, NJ Office
One MetLife Way, Whippany, NJ, United States, 07981
What you need to know about the NYC Tech Scene
As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.
Key Facts About NYC Tech
- Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
- Key Industries: Artificial intelligence, Fintech
- Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
- Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory
