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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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Posted 5 months ago
Applications closedJaltrix Data
Remote
Chicago, United States (UTC-6)
ML models are only as good as their labels. A classification model trained on annotations where 15% of the labels are wrong will learn the mistakes. O...
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Posted 5 months ago
Applications closedKolvex Cloud
Remote
New York, United States (UTC-5)
Cloud bills surprise companies every month. Training job costs spike unpredictably. Spot instance savings evaporate when availability drops. Reserved...
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Posted 5 months ago
Applications closedOrbio AI
Remote
Chicago, United States (UTC-6)
Our product is a clinical decision support system used by 40 hospitals across the Midwest. The models behind it predict patient deterioration, flag dr...
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Posted 5 months ago
Applications closedKelvix Systems
Remote
New York, United States (UTC-5)
Commodity traders pay millions for satellite imagery that tells them crop yields before harvest reports. Insurance companies use it to assess storm da...
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Posted 5 months ago
Applications closedMendra Intelligence
Remote
Chicago, United States (UTC-6)
Our fraud detection models flag 800 transactions per day as potentially suspicious. Most of them aren't. As a transaction monitoring analyst, you'll i...
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Posted 5 months ago
Applications closedOrvix Works
Remote
New York, United States (UTC-5)
Retailers hold $1.5 trillion in excess inventory globally. Every unsold item represents tied-up capital, warehouse costs, and eventually, markdowns th...
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Posted 5 months ago
Applications closedPaleon Data
Remote
Berlin, Germany (UTC+1)
Insurance companies need to price climate risk 30 years into the future. Traditional actuarial models use historical loss data that no longer reflects...
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Posted 5 months ago
Applications closedUlvex Systems
Remote
New York, United States (UTC-5)
When an ML model misbehaves in production, the clock starts ticking. Customer trust erodes with every bad prediction served. Our observability platfor...
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Posted 5 months ago
Applications closedWavion Intelligence
Remote
Berlin, Germany (UTC+1)
Product catalogs are only searchable if the taxonomy makes sense. But taxonomies evolve — new product categories emerge, old ones become obsolete, and...
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Posted 5 months ago
Applications closedZaltex Data
Hybrid
New York, United States (UTC-5)
Retailers deciding where to open the next store need more than foot traffic data. They need AI that combines demographic trends, competitor proximity,...
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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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