Data Scientist

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Scientist with 5+ years of experience, offering $46-$55 per hour for an onsite, full-time position. Key skills include Python, SQL, machine learning, and data visualization. A Bachelor’s or Master’s degree is required.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
440
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🗓️ - Date discovered
September 27, 2025
🕒 - Project duration
More than 6 months
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🏝️ - Location type
On-site
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📄 - Contract type
Unknown
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🔒 - Security clearance
Unknown
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📍 - Location detailed
Cary, NC
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🧠 - Skills detailed
#Deployment #Visualization #NLP (Natural Language Processing) #"ETL (Extract #Transform #Load)" #TensorFlow #AWS (Amazon Web Services) #Data Science #Model Deployment #Clustering #Snowflake #Datasets #Forecasting #Data Analysis #Libraries #Cloud #Classification #SQL (Structured Query Language) #Python #Azure #BI (Business Intelligence) #Pandas #Automation #Statistics #ML (Machine Learning) #Programming #Regression #Data Modeling #Microsoft Power BI #Data Processing
Role description
Job Title: Data Scientist Location: Onsite, Full-Time Experience Required: 5+ years Education Required: Bachelor’s and/or Master’s degree Internship Experience Accepted: Yes Compensation: $46-$55 per Hour Position’s Contributions to Work Group: A Data Scientist is responsible for analyzing large volumes of structured and unstructured data to extract actionable insights, build predictive models, and support data-driven decision-making. This role blends statistical expertise, programming skills, and business acumen to solve complex problems and drive innovation. Typical Task Breakdown: • Data Collection & Preparation: Gather, clean, and validate data from various sources to ensure quality and usability • Exploratory Data Analysis: Identify trends, anomalies, and patterns in large datasets • Model Development: Design and implement machine learning models (e.g., regression, classification, clustering, NLP) to support forecasting and decision-making • Data Visualization: Create dashboards and reports using tools like Power BI, etc., to communicate findings • Automation & Optimization: Develop scripts and tools to automate data processing and model deployment • Collaboration: Work cross-functionally with product, engineering, and business teams to align data initiatives with strategic goals • Research & Innovation: Stay current with emerging technologies and methodologies in data science and apply them to business challenges Team Interaction: Primarily working with 10+ team members (technical team and business partners) Required Technical Skills (Required): • Proficiency in Python, SQL, and data science libraries (e.g., Pandas, Scikit-learn, TensorFlow) • Strong foundation in statistics, probability, and machine learning • Familiarity with cloud platforms (e.g., Azure, AWS, Snowflake) and data modeling • Excellent communication skills to explain technical concepts to non-technical stakeholders Soft Skills (Required): • Excellent communication • Business acumen