Data Scientists extract insights from data to drive business decisions — using statistics, machine learning, and visualization. The role has evolved from pure analytics to include ML model building, experimentation design, and increasingly, LLM application development.
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Ritually
TalentProof
Ritually
This is a founding applied-AI role. You'll be building our core data pipeline and intelligence layer with the founding team from 0-1. You'll be tackling our largest technical challenges across technologies.
We are hiring in NYC, Denver, Bangalore, Hyderabad, or Mumbai.
Nice to have
These roles overlap with data scientist jobs — click any job to see details and apply.
Ritually
Enzigma
TalentProof
TalentProof
Ritually
This is a founding full-stack role. You'll be building our application with the founding team from 0-1. You'll own features and infra end to end and across technologies. You'll also own how we build: ensuring our AI development workflow is fast, dependable and secure.
We are hiring in NYC, Denver, Bangalore, Hyderabad, or Mumbai.
Nice to have
Get assessed in these skills to stand out when applying for data scientist jobs
Yes, though the role has evolved. Pure analytics roles are being augmented by AI tools, but Data Scientists who can build ML models, design experiments, and communicate insights remain highly valued. The intersection of data science and LLM applications is the fastest-growing niche.
Data Analysts focus on SQL, dashboards, and descriptive analytics. Data Scientists additionally build predictive models, run experiments (A/B testing), and use ML. DS roles typically require Python and statistics; DA roles emphasize SQL and visualization tools.
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