Finance & Data Analytics Intern

10x Genomics•Pleasanton, CA

7h•$23 - $40

About The Position

At 10x Genomics, everything we do is driven by our mission: to accelerate the mastery of biology to advance human health. We provide the scientific community with technologies of the highest caliber that enable experimentation at fundamental single-cell resolutions and massive scale. Our tools are cited in more than 10,000 research papers, ultimately transforming how science understands, treats, and eradicates disease. The Strategic Finance & Analytics team sits at the intersection of business strategy and data science, supporting executive decision-making through actionable data-driven insights. The team takes pride in the operational excellence of the Finance organization, and continuously seeks to improve the efficiency and efficacy of core business processes and systems. We are currently undertaking a transformation to modernize our data stack—moving from legacy manual processes to automated, AI-ready pipelines. We are looking for someone who will leverage their technical ability to make an outsized impact on business strategy. You might be a CS major interested in how businesses work, or a Finance major who taught themselves to code because Excel wasn't enough. You should be able to discuss a project, GitHub repo, or tool you built that solved a specific problem. We don’t expect you to know everything on day one, but we expect you to be a first-principles thinker who can take a vague objective, figure out the solution, and ship code that works.

Requirements

Educational Background: Pursuing a degree in Computer Science, Engineering, Math, Economics, or Finance. Candidates in their junior or senior year preferred.
Technical Proficiency: Strong ability in Python is required. Experience with SQL, version control (Git), and LLM prompt engineering is highly preferred, but aptitude to learn quickly is acceptable.
Business Acumen: You should understand intuitively how a business makes money and be eager to learn the mechanics of financial statements.
High Agency: You thrive with minimal supervision. When you hit a roadblock, you Google it, read the documentation, and find a way through.
Analytical Rigor: Experience with applied statistics or machine learning (regression analysis, time series, supervised and unsupervised models) is a strong plus.
Communication Skills: Outstanding communication and interpersonal skills, with the ability to present technical data to senior management and non-technical audiences.

Responsibilities

Data Pipeline Engineering: Write clean, scalable Python and SQL to move data out of fragile local files, transform it into structured, well-documented datasets, and automate ingestion into Snowflake.
Process Automation: Identify high-friction manual Finance workflows and automate the end-to-end process to reduce cycle time, error rates, and reliance on one-off spreadsheets.
Financial Modeling: Support revenue and cash flow forecasting, shifting models toward spreadsheet-based assumptions backed by robust, automated data pipelines.
Dashboards & Insights: Build elegant, automated dashboards that make key company metrics self-serve and consistent across the organization.