AI/ML Engineer

⭐ - 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.
🌎 - Country
United States
πŸ’± - Currency
$ USD
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πŸ’° - Day rate
520
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πŸ—“οΈ - Date discovered
August 27, 2025
πŸ•’ - Project duration
Unknown
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🏝️ - Location type
Unknown
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πŸ“„ - Contract type
Unknown
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πŸ”’ - Security clearance
Unknown
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πŸ“ - Location detailed
Arizona, United States
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🧠 - 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