Intern – Marketing Data Science & Experimentation (MoneyLion, FinTech

Job Title: Masters Intern Data Science & Analytics (Data Engineering - Lean)
Location New York City Office

About Gen

Gen (Norton, Avast, LifeLock, MoneyLion) is a global company powering Digital Freedom across cybersecurity, identity, privacy, optimization and financial wellness.

MoneyLion, part of Gen Digital, is a leader in financial technology powering the next generation of personalized products, content, and marketplace technology, with a top consumer finance super app, a premier embedded finance platform for enterprise businesses, and a world-class media arm.

GOBankingRates, also part of Gen, is a personal finance news and features website dedicated to helping visitors Live Richer—turning financial goals into milestones and money dreams into realities. Its content is regularly featured on top-tier outlets including MSN, Yahoo!, FOX Business, CNBC, and Business Insider, and it works hand-in-hand with MoneyLion’s platform to connect consumers with smarter financial decisions at scale.

If this sounds like you, we’d love you to be part of Gen.

How We Work
Our hybrid work model (3 days in New York City office) gives us the face-to-face time to have creative conversations, meaningful meetings, make quick decisions, and build relationships. At the same time, it offers flexibility you need to focus and do your best work.

About the Role:
Reporting to the Senior Data Scientist, the Data Science & Analytics Intern (Data Engineering – Lean) will support our Data Science & Analytics team with a strong focus on data engineering and practical analytics work. Based in our New York City office, this full-time 10-week internship (approximately 40 hours per week) will give you hands-on experience with modern tools such as dbt, Feast, Snowflake, and Looker to build and maintain analytical datasets, support feature creation, and deliver dashboards and ad-hoc analyses that inform business decisions across MoneyLion and the broader Gen ecosystem.

Key Responsibilities:

• Collaborate with data scientists, analysts, and data engineers to understand data needs, metrics, and business questions.

• Develop and maintain SQL queries to extract, join, and aggregate data from our Snowflake data warehouse.

• Assist with data ingestion, cleaning, and preprocessing for analytics use cases, including building dbt models and tests for core transformations.

• Help define, populate, and maintain feature tables in Feast to support analytics and downstream machine learning workflows.

• Perform exploratory data analysis (EDA) in Python (pandas, NumPy, notebooks) to profile datasets, identify trends, and surface data quality issues.

• Build or refine Looker explores, Looks, and dashboards that communicate results clearly and enable stakeholder self-service.

• Document datasets, dbt models, Feast feature definitions, and analysis steps to ensure reproducibility and knowledge sharing across the team.

• Participate in regular stand-ups, sprint reviews, and code or query reviews to gather feedback and iterate on work.

• Occasionally support simple modeling tasks (e.g., feature engineering, train/test splits, basic evaluation) under guidance, while keeping primary focus on data engineering and analytics.

Objectives and Success Measures (examples):

• Deliver high-quality, well-tested dbt models and SQL queries that are adopted by the team.

• Contribute at least one production-ready dataset or dashboard used regularly by stakeholders.

• Demonstrate increasing independence in exploring data, scoping small tasks, and estimating effort.

• Communicate findings clearly in writing, dashboards, and short presentations to non-technical partners.

About you:

Education:

• Currently enrolled in a Bachelor’s or Master’s program in Computer Science, Data Science, Statistics, Engineering, or a related field.

Experience:

• Experience (through coursework, projects, or prior internships) using SQL and relational data modeling (tables, joins, primary/foreign keys).

• Experience using Python for data manipulation and analysis (e.g., pandas, NumPy, Jupyter).

• Exposure to working with real-world datasets, including dealing with imperfect or messy data.

Skills:

• Working knowledge of SQL and relational database concepts.

• Proficiency in Python for data analysis (pandas, NumPy, notebooks).

• Familiarity with at least one BI or data visualization tool, with strong interest in learning Looker if not already experienced.

• Ability to reason about data quality issues, edge cases, and trade-offs when working with real-world data.

• Strong written and verbal communication skills and willingness to ask clarifying questions.

• Nice to have:

  • Experience with Snowflake or another cloud data warehouse (BigQuery, Redshift, etc.).

  • Exposure to dbt (models, tests, documentation, or dbt Cloud/CI).

  • Exposure to a feature store such as Feast or interest in learning feature-store concepts.

  • Experience building dashboards or explores in Looker, including any LookML basics.

  • Familiarity with Git-based workflows (branches, pull requests, code review).

  • Basic understanding of statistics or introductory machine learning concepts.

Personal Attributes:

• Ability to thrive in a fast-paced, high-tech environment and manage complex problems.

• Curious, proactive, and eager to learn new tools and concepts in data engineering and analytics.

• Collaborative mindset with a willingness to take feedback and iterate quickly.

• Organized and detail-oriented, with a focus on producing reliable, well-documented work.

Compensation (this is only for the US )

The hourly rate for this position is $30 USD per hour. Base pay is one component of Gen's total compensation package, which may also include benefits such as 401(k) match, health insurance options, disability coverage, life insurance, and paid time off, depending on role type and eligibility. Actual compensation will vary based on a candidate’s qualifications, experience, skills, and competencies related to the role.

What’s next:
Your CV will be reviewed together by the recruiter and hiring manager to assess the scope of your role, the impact you’ve delivered, and how your experience aligns with the position. If shortlisted, the recruiter will invite you to an initial Zoom conversation to discuss your background, what’s compelling you to Gen, and walk you through the interview process.

Important Application Note – When you apply, please include your current city and state and let us know work status, e.g. visa status, green card etc.

Gen is an equal opportunity employer, and we’re committed to fair, inclusive practices at every stage of the candidate and employee journey. Employment decisions are based on merit, experience and business needs.

Gen is an equal opportunity employer, and we’re committed to fair, inclusive practices at every stage of the candidate and employee journey. Employment decisions are based on merit, experience and business needs.