Product Intern – Data Science x Product Ops
We’re on the hunt for curious, hands-on folks who thrive on solving real-world problems. You’ll start by getting your hands dirty — annotating images, clustering outlets, tagging data — the gritty work that powers our ML systems and builds domain depth. As you ramp up, you'll move into more complex tasks: running experiments, writing logic, and shaping how our next-gen, ML-powered CPG tools behave. If you're analytical, adaptable, and excited about working at the intersection of data, tech, and product — we want to hear from you.
For one in the Seat:
Responsibilities:
1.Analyze product and user behavior data to identify trends, gaps, and improvement opportunities
2.Support product managers in performance tracking, product readiness, and user research.
3.Execute critical groundwork like image annotation, outlet clustering, data tagging, and documentation
4.Contribute to product experiments, testing, and model input/output validation
5.Use Excel and internal tools to build dashboards, reports, and performance views
6.Run analyses on internal platforms for insights and client-facing deliverables
7.Leverage your data science foundation (Python, pandas, ML basics) to support model design and tooling
8.Collaborate across product, design, engineering, and business teams to bring clarity to decision making.
Who we're looking for:
1.Strong problem-solving and analytical mindset
2.Proficiency in MS Excel (pivot tables, formulas, charts, VLOOKUP) the usual
3.Exposure to Python, pandas, Jupyter notebooks, or ML concepts — you don’t need to be a wizard, but you should be hungry to learn
4.Comfortable with hands-on grunt work and iterative workflows
5.Curiosity about how products are built, scaled, and improved through data
6.Team player who communicates well and thrives in slightly chaotic but high-energy setups.
7.Bonus: Prior exposure to SaaS, CPG, or product management