---
title: 'Data Jobs'
canonical: 'https://feeny.ai/jobs/data'
type: 'role'
---

# Data Jobs

> Turn raw data into models, metrics, and decisions.

- **Open roles:** 6,454
- **Typical salary:** $130K–$205K (US median base, mid–senior)
- **Top skills:** SQL, ML, Experimentation
- **Common tools:** Python, dbt, Snowflake
- **Page:** https://feeny.ai/jobs/data

## Data specializations

- [Data Science](https://feeny.ai/jobs/data/data-science) — 1,369 open roles
- [Data Engineering](https://feeny.ai/jobs/data/data-engineering) — 1,253 open roles
- [Machine Learning](https://feeny.ai/jobs/data/machine-learning) — 1,086 open roles
- [Data Analyst](https://feeny.ai/jobs/data/data-analyst) — 1,012 open roles
- [Research](https://feeny.ai/jobs/data/research) — 753 open roles
- [Quantitative Research](https://feeny.ai/jobs/data/quant) — 624 open roles
- [Analytics Engineering](https://feeny.ai/jobs/data/analytics-engineering) — 269 open roles
- [Business Intelligence](https://feeny.ai/jobs/data/bi) — 124 open roles

## Data career path

**Where everyone starts**

- Data Analyst — $80–$120K · 569 open
- Data Scientist — $120–$170K · 1,139 open
- Senior Data Scientist — $160–$230K · 334 open

**Individual contributor track**

- Staff Data Scientist — $210–$300K · 128 open
- Principal Data Scientist — $280–$400K · 34 open

**Management track**

- Data Science Manager — $200–$290K · 65 open
- Director of Data — $260–$380K · 18 open
- VP of Data — $350–$500K · 0 open

## Top companies hiring data roles

- [Launch Potato](https://feeny.ai/companies/launch-potato) — 54 open roles
- [Exadel](https://feeny.ai/companies/exadel) — 66 open roles
- [Point72 ](https://feeny.ai/companies/point72) — 73 open roles
- [Faculty](https://feeny.ai/companies/faculty) — 29 open roles
- [Stevens Capital Management LP](https://feeny.ai/companies/stevens-capital-management-lp) — 16 open roles
- [Artefact](https://feeny.ai/companies/artefact) — 38 open roles
- [Jump Trading](https://feeny.ai/companies/jump-trading) — 29 open roles
- [Qube Research & Technologies](https://feeny.ai/companies/qube-research-technologies) — 57 open roles
- [WorldQuant](https://feeny.ai/companies/worldquant) — 33 open roles
- [Exadel Inc (Website)](https://feeny.ai/companies/exadel-inc-website) — 29 open roles
- [LG AI Research](https://feeny.ai/companies/lg-ai-research) — 16 open roles
- [IMC](https://feeny.ai/companies/imc) — 39 open roles

## Data jobs: common questions

### What does a data scientist do?

A data scientist finds the signal in a company's data using statistics, experiments, and models, then turns it into decisions the business can act on. That runs from a data analyst answering questions with SQL and dashboards to a scientist building and shipping models. The exact focus depends on the team, from analytics to machine learning to research.

### How do I become a data scientist?

Common paths in are a quantitative degree, a bootcamp, or moving up from a data analyst role after showing you can model and experiment. What teams look for is the ability to go from a messy question to a defensible answer: SQL, statistics, and the judgment to know when a result is real. A portfolio of real analysis helps.

### What is the data career path?

The usual path runs analyst to data scientist to senior, owning harder problems at each step. Above senior it splits: you can stay hands-on as a Staff or Principal Data Scientist on the most important models, or move into leadership as a Data Science Manager, Director, and VP of Data building the team and strategy.

### Which skills and tools should a data scientist learn?

SQL and Python are the floor, with statistics and data modeling right behind. Machine learning and experimentation are what raise the ceiling toward senior. On tools, most teams work in a warehouse like Snowflake or BigQuery with dbt, notebooks in Python, and BI in Looker or Tableau. Experimentation tools like Statsig show up on product-facing teams.

### Do you need a degree to work in data?

It helps more here than in some fields, since the statistics and modeling have real depth, and many data scientists have a quantitative degree. That said, plenty came through bootcamps or self-study plus a strong portfolio. The bar at hiring time is whether you can actually do the analysis, not the credential.

### How much do data scientists make?

Pay ranges by level, location, and company. In the US a mid-level data scientist commonly lands in the range shown on this page, Staff and Principal roles go higher, and leadership adds equity on top of base at larger companies. The salary bands here are illustrative; the open roles listed are real postings.

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_Source: https://feeny.ai/jobs/data_