Data Science Intern
Partly
Data Science Intern
Partly
Automotive parts data platform enabling marketplace
Note: Partly is headquartered in Austin, TX with offices in London, UK, Christchurch, NZ and Auckland, NZ. Wherever you're based, we'll connect you with your nearest office for onboarding, and fly you to join the full team for our quarterly "Season Openers" (we cover travel and accommodation). If you're relocating to join us, we can also assist with relocation costs.
Partly is building the infrastructure for anyone to repair anything. We believe everything built should be repairable, and we're building frontier AI to put repair knowledge to work, starting with the $2tn automotive market.
Our model, Interpreter, is the first AI purpose-built to understand repair. Trained on 1M+ car models and 1B+ parts, it reads a repair job the way an estimator does, resolves damage into the exact purchasable part, and shows its reasoning with a confidence score. On real production jobs, an estimator working with Interpreter reaches 98.8% parts-list accuracy, against 92.1% with today's tools. It powers PartlyRepair, used by collision shops, workshops and suppliers to take the admin off the job; PartlyLabs, the agentic infrastructure enterprises use to deploy Interpreter across their own workflows; and a developer API.
Founded by ex-Rocket Lab engineers, we've raised a $50m Series B led by DST Global (Anthropic, Airbnb, Meta, TikTok, Spotify), with Blackbird Ventures, WNDR, Activant Capital, Icehouse Ventures, Square Peg, Airtree and Ecliptic Venture Capital. Hear it from the team: Why Partly exists and AI at Partly.
🖍️ This role
As a Data Science Intern, you'll work alongside our Applied ML and DataQA teams to help make sense of the technical problems behind Partly's core vehicle and parts workflows. You'll be paired with experienced data scientists and engineers who will mentor you as you dig into messy, real-world data and turn it into clear, useful analysis.
The work sits between data science, domain analysis, and product. You'll help investigate why things like parts validation, parts ordering, automatching, and variant handling become difficult or unreliable, and you'll help quantify how often those problems happen and how much they matter. This is not dashboards for the sake of dashboards, and it is not pure model training. It's hands-on, investigative work on real problems with real impact.
This is an internship for someone early in their journey who learns by doing. Expect to work directly with SQL and Python, ask good questions, build lightweight tools or analyses, and see your findings help the team decide what to fix next.
Dig into real parts data. Help build a data-backed understanding of the problems that make parts validation, parts ordering, and automatching harder, with guidance from your mentor.
Help quantify problem types. Assist in breaking broad issues (for example, "variants are messy") into specific, measurable categories and counting how often each one shows up.
Measure where quality is lost. Use SQL, Python, sampling, and internal tools to help estimate accuracy, failure rates, and impact across makes, providers, and part groups.
Turn analysis into something useful. Help produce clear findings that Applied ML, Product, and DataQA can actually act on.
Build lightweight tooling. Pitch in on scripts, small dashboards, and review workflows that help others see and understand parts problems more clearly.
Learn how the team works. Partner with Applied ML, DataQA, and Product teams, and learn how a high-velocity, low-bureaucracy team operates.
Get the basics right. Produce reproducible analyses, write clear notes, and ask thoughtful questions that make your work easy to build on.
Solid analytical fundamentals. You're studying or have recently studied data science, statistics, computer science, mathematics, engineering, or a related field, and you can reason carefully about data.
Working SQL and Python. Through coursework, projects, or prior experience, you can query data and write code to analyze it. You don't need to be an expert, but you should be comfortable getting your hands dirty.
Good problem decomposition. You enjoy taking a vague or messy question and breaking it into smaller, answerable pieces.
Curiosity about how things really work. You like understanding the "why" behind a problem, not just producing a chart, and you're comfortable with data that isn't clean or fully labeled.
Clear communicator. You can explain what you found and why it matters, ask for help when you need it, and take feedback well.
Bias for learning. You want to be stretched, you take ownership of your growth, and you're excited to work on hard, real-world problems rather than tidy textbook ones.
(Bonus) Any exposure to classification problems, data quality or QA work, entity matching, catalog data, automotive data, or working alongside ML or human-in-the-loop systems.
Please note: if you don't have all the skills or experience listed above but believe you could be outstanding in this role, please still consider applying. Many people count themselves out. We'd love the chance to learn more about you and why you're exceptional.
Healthy, Catered Lunches - Enjoy fresh, healthy lunches every workday in our Auckland, Christchurch, London and Austin offices. With no meal prep needed, you can eat, connect, and refuel with your team. (And yes, snacks and drinks are always on hand.)
Healthy Body, Healthy Mind - We care about performing at our peak. Every team member gets a $1,500 annual wellness allowance (or local equivalent) on a Partly-branded card. Use it on things such gym memberships, rock climbing, physio, massage, GP visits, prescriptions; anything that you or your family, need!
Family Comes First - Primary caregivers receive 3 months of fully paid parental leave, plus a flexible return-to-work (four days on full pay for your first three months back).
Getting Here Is On Us - If you commute to a Partly office or co-working space, choose from a paid 24/7 car park or commute allowance. One less thing to think about!
Workspaces That Inspire - Our brand new, architecturally designed offices are built for collaboration and creativity, with great coffee, social spaces, and some of the best cafes a few steps away.
Office-First with Flexibility - In cities where we have an office (Christchurch, Auckland, London, Austin), we default there every day. This let's us move faster, make better decisions and build strong relationships. We also operate with a very high trust environment, so you can manage your time around your life, and flex your schedule to get your best work done.
We Celebrate Together - From weekly happy hours and monthly lunches to quarterly season openers and an annual global offsite, we make time to connect, celebrate, and have fun as one team.
If you are relocating from overseas or domestically to Partly HQ, we offer a generous relocation allowance to support your move
Partly connects buyers and sellers of automotive parts through a B2B platform that serves as an online marketplace. It builds a global data infrastructure for the automotive parts industry, enabling manufacturers and retailers to organize, manage, and distribute parts data. The company uses data science and algorithms to process and standardize parts information from multiple sources, making it easier to find the right parts. Its platform treats data as the backbone of the ecosystem, supporting parts catalogs, data management, and supply chain transparency. Partly operates in New Zealand, Australia, and Europe with a global team and has attracted significant investor funding, helping it grow into a fast-growing startup in its region. The goal is to simplify the process of locating and acquiring automotive parts by improving data quality, interoperability, and connectivity across the parts ecosystem.
Explore more opportunities at Partly