

AI/ML Engineer
β - Featured Role | Apply direct with Data Freelance Hub
This role is for an AI/ML Engineer in the reinsurance domain, offering a contract of "X months" at a pay rate of "$X/hour." Key skills include Python, SQL, machine learning, and data visualization. Experience with actuarial models is essential.
π - Country
United States
π± - Currency
$ USD
-
π° - Day rate
520
-
ποΈ - Date discovered
August 27, 2025
π - Project duration
Unknown
-
ποΈ - Location type
Unknown
-
π - Contract type
Unknown
-
π - Security clearance
Unknown
-
π - Location detailed
Arizona, United States
-
π§ - Skills detailed
#Big Data #Storytelling #Spatial Data #Cloud #Spark (Apache Spark) #Hadoop #Tableau #Visualization #Pandas #Regression #Matplotlib #NLP (Natural Language Processing) #GIT #ML (Machine Learning) #Time Series #Model Deployment #Data Wrangling #R #AI (Artificial Intelligence) #AWS (Amazon Web Services) #Microsoft Power BI #SQL (Structured Query Language) #Data Engineering #BI (Business Intelligence) #NumPy #Clustering #Deployment #Azure #Data Integrity #Data Science #Python #Classification #"ETL (Extract #Transform #Load)" #SAS #Data Pipeline #Programming #Forecasting
Role description
Job description
Role Overview
We are seeking a highly analytical and detailoriented Data Scientist to join our team in the reinsurance domain The ideal candidate will leverage data to drive insights into risk modeling pricing strategies claims analysis and portfolio optimization This role requires strong technical expertise business acumen and the ability to communicate complex findings clearly
Technical Skills Primary
Programming Languages Python Pandas NumPy Scikitlearn SQL
Statistical Modeling Machine Learning Regression Classification Clustering Time Series Forecasting
Data Visualization Power BI Tableau Matplotlib Seaborn
Big Data Technologies Spark Hadoop basic understanding
Cloud Platforms Azure or AWS especially for data pipelines and model deployment
Data Engineering ETL processes data wrangling and feature engineering
InsuranceReinsurance Domain Knowledge Exposure to actuarial models risk assessment and claims analytics
Technical Skills Secondary Nice to Have NOT MANDATORY
R or SAS for statistical analysis
Experience with Natural Language Processing NLP
Familiarity with geospatial data and mapping tools
Knowledge of Monte Carlo simulations and stochastic modeling
Experience with Git and CICD pipelines
Exposure to regulatory frameworks Solvency II IFRS 17
Soft Skills
Strong problemsolving and critical thinking abilities
Excellent communication and storytelling skills for nontechnical stakeholders
Collaborative mindset with crossfunctional teams actuarial underwriting IT
Ability to manage multiple projects and prioritize effectively
Curiosity and continuous learning attitude
High attention to detail and data integrity
Qualifying Questions
Can you describe a project where you applied machine learning to solve a business problem in the insurance or financial domain
How do you ensure the quality and reliability of your data before building models
Have you worked with actuarial teams or underwriting departments before If yes how did you contribute to their decisionmaking process
Skills
Mandatory Skills : AI/GenAI Research
Job description
Role Overview
We are seeking a highly analytical and detailoriented Data Scientist to join our team in the reinsurance domain The ideal candidate will leverage data to drive insights into risk modeling pricing strategies claims analysis and portfolio optimization This role requires strong technical expertise business acumen and the ability to communicate complex findings clearly
Technical Skills Primary
Programming Languages Python Pandas NumPy Scikitlearn SQL
Statistical Modeling Machine Learning Regression Classification Clustering Time Series Forecasting
Data Visualization Power BI Tableau Matplotlib Seaborn
Big Data Technologies Spark Hadoop basic understanding
Cloud Platforms Azure or AWS especially for data pipelines and model deployment
Data Engineering ETL processes data wrangling and feature engineering
InsuranceReinsurance Domain Knowledge Exposure to actuarial models risk assessment and claims analytics
Technical Skills Secondary Nice to Have NOT MANDATORY
R or SAS for statistical analysis
Experience with Natural Language Processing NLP
Familiarity with geospatial data and mapping tools
Knowledge of Monte Carlo simulations and stochastic modeling
Experience with Git and CICD pipelines
Exposure to regulatory frameworks Solvency II IFRS 17
Soft Skills
Strong problemsolving and critical thinking abilities
Excellent communication and storytelling skills for nontechnical stakeholders
Collaborative mindset with crossfunctional teams actuarial underwriting IT
Ability to manage multiple projects and prioritize effectively
Curiosity and continuous learning attitude
High attention to detail and data integrity
Qualifying Questions
Can you describe a project where you applied machine learning to solve a business problem in the insurance or financial domain
How do you ensure the quality and reliability of your data before building models
Have you worked with actuarial teams or underwriting departments before If yes how did you contribute to their decisionmaking process
Skills
Mandatory Skills : AI/GenAI Research