Data Science Intern (Summer/Fall 2025) [US Only]

About Grantx Grantx is building the operating system that helps startups, municipalities and research teams find, win, and manage non-dilutive funding. Our AI-driven platform surfaces the right opportunities in seconds, predicts win-probability, and automates post-award compliance. We’re a seed-stage GovTech/FinTech company backed by domain-expert angels, headquartered in Portland, ME with a distributed team across North America. The Role You’ll join our Data pod (Marco + Venky) to improve the quality, coverage and reliability of the world’s largest structured database of public- and private-sector grants. You’ll ship production code, not slide decks; your analysis will surface directly in our product and dashboards. Expect fast iterations, measurable impact, and mentorship from engineers who care about craft. What You’ll Do • Design and run experiments to raise deterministic-filter coverage for critical grant fields (award ceiling, close date, funder id) • Prototype heuristics and ML classifiers that detect cyclical grants and flag conflicting data during ingestion • Build validation pipelines in Python (Pandas, Polars) and orchestrate them in our Dagster environment • Create insight reports on NOFO (Notice of Funding Opportunity) prevalence across grant types to guide roadmap decisions • Present findings in concise, KPI-anchored reviews to the COO and product leadership You Might Be a Fit If • You’re pursuing (or recently completed) a B.S./M.S. in Data Science, Statistics, Computer Science, or related field • You’ve completed at least one significant project using Python data-stack (Pandas, NumPy, scikit-learn or similar) • You can write clean SQL and are comfortable reasoning about schema design and data lineage • You enjoy turning messy, real-world datasets into actionable metrics and can explain your approach in plain language • You thrive in fast-moving, ambiguity-heavy environments and value shipping iterations over chasing perfection Bonus Points • Experience with Dagster, Airflow, or other data-orchestration tools • Familiarity with document understanding models (LayoutLM, DiT) or language-model evaluation • Prior work involving government or financial datasets What We Offer • Competitive hourly rate and optional equity stipend for longer engagements • Fully remote culture with quarterly in-person meetups (travel covered) • Dedicated mentor and weekly learning budget (books, courses, conferences) • Opportunity to convert to full-time role as we scale Apply tot his job