AI ML Engineer

Job Category: Engineer
Job Type: Hybrid
Job Location: Dallas Texas
Compensation: Depends on Experience
W2: W2-Contract Only; Kindly note that applications on a C2C basis will not be considered for this role.
Job Description
Job Description:

• 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 problem solving 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
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