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Browse remote Pandas positions — data engineering, feature engineering, and Python data science roles at AI-first companies.
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Full-time roles and fixed-scope freelance missions, matched to your AI skills.
Posted 4 months ago
Applications closedJaltrix Data
Remote
New York, United States (UTC-5)
Not all labeling tasks are equally hard, and not all annotators are equally accurate on all tasks. Matching the right annotator to the right task — an...
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Posted 4 months ago
Applications closedJarvik Solutions
Remote
Chicago, United States (UTC-6)
Customer success teams are reactive by default — they reach out when something goes wrong. The opportunity cost of that approach is enormous: accounts...
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Posted 4 months ago
Applications closedElara Intelligence
Remote
New York, United States (UTC-5)
An AI system that cannot explain its decisions is not explainable — it is just undocumented. Explainability in production means capturing not just the...
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Posted 4 months ago
Applications closedEvorra Systems
Remote
New York, United States (UTC-5)
Every infrastructure change carries risk — but most organizations approve changes based on gut feel and verbal assurances. The engineer says the firew...
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Posted 4 months ago
Applications closedFarion Data
Remote
New York, United States (UTC-5)
Last-click attribution is dead. Privacy changes killed the cross-device tracking that made it marginally defensible, and it was always directionally w...
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Posted 4 months ago
Applications closedFelvix Tech
Remote
London, United Kingdom (UTC+0)
Regulatory sandboxes — formal programs where financial services and fintech companies can test AI products with limited regulatory oversight before fu...
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Posted 4 months ago
Applications closedFynix Studio
Remote
New York, United States (UTC-5)
Product-led growth depends on signals: which free users are showing buying intent, which accounts have expansion potential, which activated users are...
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Posted 4 months ago
Applications closedGlyph Systems
Remote
New York, United States (UTC-5)
Government procurement data is public but nearly unusable. Tender documents are PDF attachments with inconsistent formatting. Contract award notices v...
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Posted 4 months ago
Applications closedAxion Labs
Remote
New York, United States (UTC-5)
Clinical trials fail at 90% because the wrong patients are enrolled. Too much heterogeneity in the patient population masks treatment effects; too nar...
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Posted 4 months ago
Applications closedBolvex Solutions
Remote
Chicago, United States (UTC-6)
A surgeon deciding whether to recommend a complex procedure needs to know the patient-specific complication risk — not the population average from a t...
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Role guide
Pandas is the backbone of Python data work. Remote Pandas roles involve data cleaning, feature engineering for ML pipelines, exploratory data analysis, and building the data foundations that AI models depend on. Strong Pandas engineers are proficient in vectorised operations, memory optimisation, and integrating Pandas with the broader PyData ecosystem.
Are there remote jobs specifically requiring Pandas experience?
Pandas is rarely the only listed skill — it typically appears with Python, NumPy, and Scikit-learn in data science and ML engineering roles. Feature engineering and data pipeline positions are the most relevant.
Is Pandas enough for remote data science jobs, or do I need more?
Pandas is foundational, not sufficient alone. Most remote AI roles also require SQL, Python scripting, and at least one ML framework. Adding Scikit-learn and Spark/Dask significantly broadens your options.
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