# Data Scientist

**Company:** [Rain](https://hotfix.jobs/companies/rain)
**Location:** New York, NY
**Role:** Data Science
**Experience:** 5+ years
**Skills:** SQL, BI Tools, Python, pandas, dbt, Llm Tools, Metabase, Mode, Lightdash, Hex
**Posted:** 2026-03-24

> Owns dashboards, insights, and metric quality to drive leadership decisions from operational data. Requires advanced SQL, BI tools, 5-8+ years in analytics, and strong cross-functional communication.

## Job Description

## Responsibilities
- Build dashboards and data sources that enable self-serve – clear, trusted views that drive operating cadence and day-to-day decisions.
- Insights discovery – establish a rhythm that consistently surfaces what matters to the people who need it most.
- Own metric quality with stakeholders – partner with Product and Engineering to ensure we can answer the most important questions and ensure reliability.

## Requirements
- Structured approach to problem solving and the ability to turn fuzzy questions into crisp analysis and clear actions.
- Strong bias for action and comfort owning end-to-end analyses, from problem framing to data pulls, insights, recommendations, and follow-through.
- Excellent communication skills and experience acting as a cross-functional thought partner to both technical and non-technical audiences.
- **Advanced SQL skills**, including comfort with complex joins, edge cases, and messy schemas.
- **Advanced experience with BI tools** (Metabase, Mode, Lightdash, Hex, or similar) and designing dashboards for self-serve analytics.
- **5–8+ years** of experience in data analytics, business analytics, data science, product analytics, consulting, or related roles.

## Nice-to-Haves
- Experience in fintech, payments, card programs, or financial infrastructure.
- **Python** proficiency for analysis/automation (pandas, notebooks, lightweight pipelines).
- Strong spreadsheet skills; comfort building and QA’ing metric logic.
- Experience using **LLM tools** to accelerate analysis (e.g., classification of tickets, summarization, automated insight generation).
- Familiarity with modern data stack concepts (**dbt**, dimensional modeling, metrics layers) even if you’re not the primary owner.

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