E-Solutions
Lead Data Scientist
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Lead Data Scientist in Alpharetta, GA, with a contract length of "unknown" and a pay rate of "unknown." Key skills include Python, R, machine learning, big data technologies, and expertise in frameworks like TensorFlow and PyTorch.
🌎 - Country
United States
💱 - Currency
$ USD
-
💰 - Day rate
Unknown
-
🗓️ - Date
February 6, 2026
🕒 - Duration
Unknown
-
🏝️ - Location
On-site
-
📄 - Contract
Unknown
-
🔒 - Security
Unknown
-
📍 - Location detailed
Alpharetta, GA
-
🧠 - Skills detailed
#TensorFlow #Big Data #NumPy #Regression #R #Spark (Apache Spark) #PyTorch #Distributed Computing #Libraries #Storage #Datasets #Data Processing #Data Analysis #Pandas #Clustering #ML (Machine Learning) #Classification #Data Manipulation #Python #Data Science
Role description
Role : Lead Data Scientist
Location : Alpharetta GA
Job Responsibilities :
Hands-on experience with data analysis tools: Proficient in using tools such as Python and R for data manipulation, querying, and analysis. Skilled in utilizing libraries like Pandas, NumPy, and Scikit-Learn to perform in-depth data analysis and modeling.
Skilled in machine learning and predictive analytics: Expertise in building, training, and deploying machine learning models using frameworks such as TensorFlow and PyTorch.
Capable of performing tasks like regression, classification, clustering, and recommendation, leading to data-driven predictions and insights.
Expertise in big data technologies: Proficient in handling large datasets using big data tools such as Spark.
Skilled in employing distributed computing and parallel processing techniques to ensure efficient data processing, storage, and analysis, enabling enterprise-level solutions and informed decision-making
Role : Lead Data Scientist
Location : Alpharetta GA
Job Responsibilities :
Hands-on experience with data analysis tools: Proficient in using tools such as Python and R for data manipulation, querying, and analysis. Skilled in utilizing libraries like Pandas, NumPy, and Scikit-Learn to perform in-depth data analysis and modeling.
Skilled in machine learning and predictive analytics: Expertise in building, training, and deploying machine learning models using frameworks such as TensorFlow and PyTorch.
Capable of performing tasks like regression, classification, clustering, and recommendation, leading to data-driven predictions and insights.
Expertise in big data technologies: Proficient in handling large datasets using big data tools such as Spark.
Skilled in employing distributed computing and parallel processing techniques to ensure efficient data processing, storage, and analysis, enabling enterprise-level solutions and informed decision-making
