Fusion IT
Data Scientist
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Scientist with 8+ years of experience in retail, focusing on forecasting and predictive analytics. Contract length is unspecified, with a pay rate of "TBD." Key skills include Python or R, time-series forecasting, and cloud platforms.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
February 17, 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
Boston, MA
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🧠 - Skills detailed
#Libraries #NumPy #AWS (Amazon Web Services) #Azure #Mathematics #Data Science #Pandas #TensorFlow #GCP (Google Cloud Platform) #Forecasting #Statistics #PyTorch #Data Modeling #Computer Science #Big Data #R #Cloud #Python
Role description
Roles & Responsibilities
• Bachelor's or master's degree in data science, Statistics, Mathematics, Computer Science, or a related field.
• 8+ years of experience in data science, with a strong focus on forecasting and predictive analytics.
• Proven experience in the retail industry, including demand forecasting, merchandising, pricing, or supply chain use cases.
• Strong proficiency in Python or R and relevant libraries (pandas, NumPy, scikit-learn, statsmodels, TensorFlow/PyTorch).
• Hands-on experience with time-series forecasting techniques and evaluation methodologies.
• Solid understanding of data modeling, feature engineering, and model lifecycle management.
• Experience working with cloud platforms (Azure, AWS, or GCP) and big data technologies is a plus.
• Excellent communication and stakeholder management skills.
Roles & Responsibilities
• Bachelor's or master's degree in data science, Statistics, Mathematics, Computer Science, or a related field.
• 8+ years of experience in data science, with a strong focus on forecasting and predictive analytics.
• Proven experience in the retail industry, including demand forecasting, merchandising, pricing, or supply chain use cases.
• Strong proficiency in Python or R and relevant libraries (pandas, NumPy, scikit-learn, statsmodels, TensorFlow/PyTorch).
• Hands-on experience with time-series forecasting techniques and evaluation methodologies.
• Solid understanding of data modeling, feature engineering, and model lifecycle management.
• Experience working with cloud platforms (Azure, AWS, or GCP) and big data technologies is a plus.
• Excellent communication and stakeholder management skills.
