Call Quest Solution
Senior Data Scientist
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior Data Scientist with a contract length of "unknown," offering a pay rate of "unknown." Key skills include Python, R, SQL, and experience in predictive modeling. A Master’s degree and 5–7 years in data science are required, preferably in insurance or financial services.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
March 24, 2026
🕒 - Duration
Unknown
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🏝️ - Location
Unknown
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
United States
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🧠 - Skills detailed
#AI (Artificial Intelligence) #GIT #Big Data #Data Science #Visualization #Azure #GDPR (General Data Protection Regulation) #Python #ML (Machine Learning) #Microsoft Power BI #Predictive Modeling #Data Privacy #Cloud #Documentation #AWS (Amazon Web Services) #Model Deployment #Strategy #Tableau #BI (Business Intelligence) #TensorFlow #Compliance #Data Analysis #A/B Testing #Deployment #Data Quality #R #Statistics #Mathematics #GCP (Google Cloud Platform) #Data Engineering #PyTorch #Monitoring #SQL (Structured Query Language) #Time Series #Model Optimization
Role description
Role Overview
We are seeking a Senior Data Scientist to build and scale advanced machine learning models that drive marketing strategy, customer insights, and business growth. This role focuses on predictive modeling, experimentation, and leveraging AI/ML (including Generative AI) to optimize customer behavior and campaign performance.
Key Responsibilities
• Build and deploy predictive models (propensity, retention, cross-sell, next best action)
• Perform exploratory data analysis, feature engineering, and model optimization
• Evaluate models using metrics like precision, recall, F1 score
• Design and execute A/B testing and experimentation frameworks
• Forecast campaign performance and validate results against actuals
• Develop and maintain ML pipelines and MLOps workflows
• Ensure data quality by partnering with data engineering teams
• Apply data privacy, compliance (GDPR/CCPA), and ethical AI practices
• Identify opportunities for model improvement and new use cases
• Automate processes and maintain clear documentation
• Translate insights into actionable business strategies
Required Qualifications
• Master’s degree in Statistics, Mathematics, Data Science, Economics, or related field
• 5–7 years of experience in data science and machine learning
• Strong hands-on experience with Python or R, SQL, and ML frameworks (scikit-learn, TensorFlow, PyTorch, etc.)
• Experience with MLOps, model deployment, and monitoring
• Familiarity with cloud platforms (AWS, Azure, or GCP) and big data tools
• Strong knowledge of advanced modeling techniques (ensemble, time series, probabilistic models)
• Experience with data visualization tools (Power BI, Tableau)
• Excellent analytical, problem-solving, and communication skills
Preferred Qualifications
• Experience in insurance or financial services
• Exposure to Generative AI in predictive modeling
• Knowledge of marketing analytics (attribution, CLV, media mix models)
• Experience with CI/CD, Git, and automated ML pipelines
• Familiarity with Bayesian methods, sequential testing, or bandit algorithms
• Understanding of risk or actuarial modeling
Role Overview
We are seeking a Senior Data Scientist to build and scale advanced machine learning models that drive marketing strategy, customer insights, and business growth. This role focuses on predictive modeling, experimentation, and leveraging AI/ML (including Generative AI) to optimize customer behavior and campaign performance.
Key Responsibilities
• Build and deploy predictive models (propensity, retention, cross-sell, next best action)
• Perform exploratory data analysis, feature engineering, and model optimization
• Evaluate models using metrics like precision, recall, F1 score
• Design and execute A/B testing and experimentation frameworks
• Forecast campaign performance and validate results against actuals
• Develop and maintain ML pipelines and MLOps workflows
• Ensure data quality by partnering with data engineering teams
• Apply data privacy, compliance (GDPR/CCPA), and ethical AI practices
• Identify opportunities for model improvement and new use cases
• Automate processes and maintain clear documentation
• Translate insights into actionable business strategies
Required Qualifications
• Master’s degree in Statistics, Mathematics, Data Science, Economics, or related field
• 5–7 years of experience in data science and machine learning
• Strong hands-on experience with Python or R, SQL, and ML frameworks (scikit-learn, TensorFlow, PyTorch, etc.)
• Experience with MLOps, model deployment, and monitoring
• Familiarity with cloud platforms (AWS, Azure, or GCP) and big data tools
• Strong knowledge of advanced modeling techniques (ensemble, time series, probabilistic models)
• Experience with data visualization tools (Power BI, Tableau)
• Excellent analytical, problem-solving, and communication skills
Preferred Qualifications
• Experience in insurance or financial services
• Exposure to Generative AI in predictive modeling
• Knowledge of marketing analytics (attribution, CLV, media mix models)
• Experience with CI/CD, Git, and automated ML pipelines
• Familiarity with Bayesian methods, sequential testing, or bandit algorithms
• Understanding of risk or actuarial modeling
