Talantix.io
Arbol•17.02.26
AI SCORE 8.5

Remote Data Scientist - Climate Risk Analytics

$95K–$125K/year
RemoteFinTech
Python•Pandas•NumPy•Machine Learning•Data Analysis•Statistical Analysis

About the Role

We are seeking a Remote Data Scientist to join Arbol, a leading climate risk coverage platform and FinTech company. In this role, you will leverage machine learning tools to model and price climate and weather risks, contributing to our mission of providing innovative solutions for businesses to analyze and mitigate exposure to climate risk. This Remote Data Scientist position offers a unique opportunity to work with diverse datasets and engage in impactful analytics.

What You'll Do

  • Collaborate within the analytics team and across departments to gain expertise in Arbol’s data and pricing infrastructure.
  • Develop and enhance models for climate and weather perils, including heat waves and severe storms.
  • Implement and evaluate pricing algorithms for various weather risks.
  • Work closely with sales and executive teams to conduct business-critical analytics.
  • Utilize your programming skills in Python and data science packages like Pandas and Numpy.

Requirements

  • BA in statistics, computer science, mathematics, or a related quantitative field.
  • Experience programming in Python and familiarity with common data science packages.
  • Strong analytical skills and experience analyzing large datasets.
  • Comfort with statistical methods such as linear regression and hypothesis testing.
  • Willingness to learn and adapt in a fast-paced environment.

Nice to Have

  • Experience with machine learning frameworks.
  • Knowledge of climate data and its applications in risk assessment.
  • Familiarity with blockchain technology and its use in operational efficiencies.

What We Offer

  • Competitive salary ranging from $95,000 to $125,000 per year.
  • Equity in a high-growth startup.
  • Comprehensive health, dental, and vision coverage.
  • 401(k) match to support your future.
  • Flexible PTO to help you recharge.

At Arbol, we value diverse perspectives and encourage candidates from non-traditional backgrounds to apply. If you require accommodations during the hiring process, please reach out to us at hr@arbol.io.

Language Requirements
EnglishC1
BasicIntermediateAdvancedNative
Why This Job8.5 of 10

This Remote Data Scientist position at Arbol offers an exciting opportunity to work at the intersection of climate risk and data science, with competitive compensation and equity in a growing startup.

Salary Range
Required
0/1
Optional
0/1
Bonus
0/1

Who Will Succeed Here

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Proficient in Python with hands-on experience in libraries like Pandas and NumPy for data manipulation and analysis, demonstrating the ability to work with large datasets effectively.

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Self-motivated and disciplined in a remote work environment, showcasing strong organizational skills to manage tasks independently while meeting project deadlines.

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Analytical mindset with practical experience in applying machine learning algorithms for statistical analysis, particularly in the context of climate data, to derive actionable insights.

Learning Resources

→Python for Data Science Handbookguide
→Machine Learning with Python for Everyonecourse
→Data Analysis with Pandasarticle

Career Path

Remote Data Scientist - Climate Risk Analytics(Now)→Data Scientist - Climate Risk Specialist(1-2 years)→Lead Data Scientist - Climate Analytics(3-5 years)

Market Overview

Market Size 2024
$50B
Annual Growth
22.5%
AI Adoption in Data Science
78%
Investment in Climate Tech
+150%
Labour Demand for Data Scientists
+30%
Avg Salary for Data Scientists
$120K

Skills & Requirements

Required
PythonPandasNumPy
Growing in Demand
Deep LearningGeospatial AnalysisData Visualization (e.g., Tableau, Matplotlib)
Declining
SASExcel VBA

Domain Trends

Increased Focus on Climate Risk Modeling
Organizations are investing heavily in predictive analytics for climate risk, with a 40% increase in demand for specialized data scientists in this area.
Integration of AI in Environmental Data Analysis
AI tools are being integrated into environmental data analysis, with 65% of companies adopting machine learning models for climate-related insights.
Growing Importance of Open Source Tools
The use of open-source tools like Python libraries for data science has increased by 50%, as companies seek cost-effective solutions for complex climate data analysis.

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