Data Scientist

We are seeking an experienced Data Scientist to design, develop, and deploy advanced AI/ML models leveraging client pricing datasets. The ideal candidate will have a strong background in statistical modeling, machine learning, and data engineering, with proven experience in building scalable solutions for pricing optimization and predictive analytics.

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• Design and implement AI/ML models for pricing optimization, elasticity analysis, and revenue forecasting.
  
• Apply advanced algorithms (e.g., regression, tree-based models, deep learning) to large-scale pricing datasets.
  

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• Perform exploratory data analysis (EDA) to identify patterns and anomalies in pricing data.
  
• Develop robust feature engineering pipelines for model accuracy and interpretability.
  

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• Collaborate with engineering teams to deploy models into production environments.
  
• Ensure scalability, performance, and compliance with client requirements.
  

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• Work closely with pricing analysts, business teams, and client stakeholders to translate business objectives into data-driven solutions.
  
• Present insights and recommendations through clear visualizations and reports.
  

Education: Degree in Data Science, Computer Science, Statistics, or related field.

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• Strong proficiency in Python, R, and ML libraries (e.g., scikit-learn, TensorFlow, PyTorch).
  
• Experience with pricing analytics, predictive modeling, and optimization techniques.
  
• Hands-on experience with SQL, big data platforms (Spark, Hadoop), and cloud services (AWS, Azure, GCP).
  
• Deep understanding of pricing strategies, elasticity modeling, and revenue management.
  
• Excellent communication and stakeholder management skills.
  

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• Experience in Insurance.
  
• Familiarity with MLOps and CI/CD pipelines for ML models.
  
• Knowledge of generative AI or advanced NLP techniques for pricing insights.
  

Seniority level: Mid-Senior level

Employment type: Full-time

Job function: Information Technology

Industries: IT Services and IT Consulting