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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 4 months ago
Applications closedZenora Labs
Remote
New York, United States (UTC-5)
Benchmarks lie. A model that scores 90% on MMLU might fail at tasks that MMLU wasn't designed to measure, and the gap between benchmark performance an...
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Posted 4 months ago
Applications closedTrivon Data
Remote
New York, United States (UTC-5)
Professional sports teams spend $180M per year on player salaries and lose an average of $22M annually to preventable soft-tissue injuries. The resear...
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Posted 4 months ago
Applications closedUelvex Cloud
Remote
New York, United States (UTC-5)
API pricing is one of the least understood levers in SaaS. Should you charge per call, per token, per outcome, or per seat? The answer depends on usag...
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Posted 4 months ago
Applications closedUnvix Works
Remote
Chicago, United States (UTC-6)
Data pipelines break at 3 AM and nobody finds out until a stakeholder notices wrong numbers in a dashboard the next morning. Data reliability engineer...
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Posted 4 months ago
Applications closedValtrix Solutions
Remote
New York, United States (UTC-5)
Commercial real estate valuations rely on cap rate comparables and DCF models built in Excel by analysts who manually pull comps from three different...
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Posted 4 months ago
Applications closedTalmion Data
Remote
New York, United States (UTC-5)
How much should you spend to acquire a user you've never seen before? If your LTV model can answer that question in the first 3 days of a user's lifec...
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Posted 4 months ago
Applications closedOrbio AI
Remote
New York, United States (UTC-5)
Finding a biomarker for early disease detection is a needle-in-a-haystack problem at genomic scale. A typical discovery project involves 500GB of mult...
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Posted 4 months ago
Applications closedOrvix Works
Remote
New York, United States (UTC-5)
Supply chains broke in 2020 and procurement teams are still rebuilding their risk detection playbooks. Our platform monitors 120,000 supplier relation...
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Posted 4 months ago
Applications closedPaleon Data
Remote
New York, United States (UTC-5)
Voluntary carbon markets depend on accurate sequestration estimates — but the current methods are 15 years old and based on sparse field measurements....
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Posted 4 months ago
Applications closedQuelion Intelligence
Remote
New York, United States (UTC-5)
The 2008 financial crisis was partly a failure of risk models that assumed normal distributions and ignored tail correlations. Our mission is to build...
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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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