Super Day - Data Science Internship

Perpay - Career's Page•Philadelphia, PA

3d•Onsite

About The Position

Perpay is seeking a Data Science Intern for the summer of 2027 to join their data team. This role involves leveraging expansive datasets to research, identify, and build features for training models. The intern will apply knowledge of modeling, statistical methodologies, and exploratory data analysis, partnering with stakeholders across various departments. The goal is to drive company growth through data-driven solutions, utilizing a tech stack including Python (scikit-learn, pandas, NumPy, statsmodels), SQL, and Redshift. The internship focuses on learning through hands-on experience, with opportunities to scope and ship real projects, present work to the team, and network with business owners.

Requirements

Currently enrolled in or will receive a Master's in Data Science, Computer Science, Computer Engineering, Information Systems, or an equivalent technical discipline with an expected graduation date between winter 2027 and summer 2028, or equivalent relevant experience.
Knowledge of machine learning and statistical research.
Experience using SQL for acquiring and transforming data.
Proficient in programming, analysis, and visualization using object-oriented programming languages (Python preferred).

Nice To Haves

Enrolled in a Master’s Degree or advanced technical degree
Previous work experience in a technical field
Experience with implementing machine learning solutions to production environments
Understanding of modern scalable data science platforms

Responsibilities

Leverage expansive data sets to research, identify, and build features to train models and drive real impact.
Apply knowledge of modeling, statistical methodologies, and exploratory data analysis.
Partner with stakeholders across Engineering, Risk, Marketing, Merchandising, and Finance.
Communicate solutions designed to drive company growth.
Get hands-on with the company's tech stack, including Python (scikit-learn, pandas, NumPy, statsmodels), SQL, and Redshift.
Introduce yourself on Slack and meet your team within the first week.
Get oriented in data sets, walk through existing models and analyses, and read the codebase to start asking questions within the first week.
Become fluent in data sets and modeling tools to explore and build independently within the first month.
Scope your first real project with a mentor, including the modeling or statistical approach and trade-offs, within the first month.
Ship your first contribution (a feature, analysis, or model improvement) within the first month.
Ship a model, feature, or analysis that the team relies on after your departure by the end of the internship.
Present your work to the broader team by the end of the internship.
Meet with various business owners across the company to build your network and understand how a data team fits into a fast-paced startup by the end of the internship.

Benefits

Hourly compensation
Espresso bar, full kitchen, weekly catered lunches, snacks, beverages, & everyday lunch essentials
One-of-a-kind office with comfortable work/lounge spaces and pleasant riverfront setting
Opportunity to gain experience at one of the fastest-growing financial startups in the country in both e-commerce & fintech, working cross-functionally.
Meaningful compensation and equity (for full-time team members)
Premium medical benefits (fully paid base plan, and very reasonable premium for the buy-up option) (for full-time team members)
5% employer 401k match (for full-time team members)
Unlimited PTO policy (for full-time team members)
Remote weeks around major holidays + extra holiday on weekends like MDW and LDW (for full-time team members)
High quality catered lunch by local chefs, 4 days / week (for full-time team members)
Gym subsidy (for full-time team members)
Paid cell phone + plan (for full-time team members)
Student loan repayment match program (for full-time team members)
Family savings match program (for full-time team members)
Relocation assistance (for full-time team members)
Generous team member discounts (for full-time team members)