MSH
Data Scientist
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Scientist with a contract length of "X months" and a pay rate of "$X/hour". Required skills include predictive modeling, data quality, machine learning, and data visualization. Industry experience in analytics is essential. Work location is "Remote/On-site".
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
December 12, 2025
🕒 - 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
Los Angeles, CA
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🧠 - Skills detailed
#ML (Machine Learning) #Predictive Modeling #Data Analysis #Compliance #Visualization #Datasets #Data Science #Data Quality #Storytelling
Role description
Role Summary:
Conducts advanced analytics, machine learning, predictive modeling, statistical analysis, and data-driven insights to support strategic and operational decision-making.
Key Responsibilities:
• Collect, clean, and preprocess datasets; ensure data quality and compliance.
• Perform exploratory data analysis to identify patterns, correlations, and anomalies.
• Design and implement predictive models, machine learning algorithms, and statistical techniques.
• Validate, tune, deploy, and monitor models in production.
• Collaborate with business and technical teams to translate business needs into analytical solutions.
• Develop and maintain dashboards, reports, and data visualizations.
• Present insights to technical and non-technical stakeholders through clear storytelling.
• Track model health, detect drift, and recommend retraining strategies.
• • Stay current with emerging trends, tools, and methodologies in analytics and data science.
Role Summary:
Conducts advanced analytics, machine learning, predictive modeling, statistical analysis, and data-driven insights to support strategic and operational decision-making.
Key Responsibilities:
• Collect, clean, and preprocess datasets; ensure data quality and compliance.
• Perform exploratory data analysis to identify patterns, correlations, and anomalies.
• Design and implement predictive models, machine learning algorithms, and statistical techniques.
• Validate, tune, deploy, and monitor models in production.
• Collaborate with business and technical teams to translate business needs into analytical solutions.
• Develop and maintain dashboards, reports, and data visualizations.
• Present insights to technical and non-technical stakeholders through clear storytelling.
• Track model health, detect drift, and recommend retraining strategies.
• • Stay current with emerging trends, tools, and methodologies in analytics and data science.
