New York Technology Partners
Data Science Specialist
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Science Specialist with 8+ years of experience, focusing on big data solutions and analytics. Contract length is unspecified, with a pay rate of "X per hour". Proficiency in Hadoop, Spark, and cloud platforms is required.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
560
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🗓️ - Date
July 9, 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
New York City Metropolitan Area
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🧠 - Skills detailed
#Spark (Apache Spark) #Data Mining #Computer Science #AWS (Amazon Web Services) #Docker #Kubernetes #"ETL (Extract #Transform #Load)" #Libraries #Predictive Modeling #Azure #Databases #Data Pipeline #Java #Data Engineering #Hadoop #MongoDB #Data Science #Data Processing #Kafka (Apache Kafka) #Apache Kafka #Pandas #Datasets #TensorFlow #BI (Business Intelligence) #ML (Machine Learning) #Big Data #Cloud #NoSQL #Python #Programming #NumPy #Scala #R
Role description
Your Impact:
Lead the development and implementation of scalable big data solutions and advanced analytics frameworks for clients.
• Work closely with cross-functional teams to define business requirements and translate them into actionable data strategies.
• Design and optimize data models and algorithms that solve complex business challenges using large-scale datasets.
• Leverage big data technologies such as Hadoop, Spark, and NoSQL databases to process and analyze large datasets.
• Build and deploy machine learning models that can be integrated into production environments to deliver real-time insights.
• Conduct advanced statistical analysis and predictive modeling to uncover trends, patterns, and opportunities within big data.
• Continuously improve data science processes, ensuring they are efficient, scalable, and aligned with business objectives.
Skills & Experience:
8+ years of experience in data science, big data engineering, or a similar field, with a strong understanding of analytics and machine learning.
• Proficiency with big data technologies such as Hadoop, Spark, Hive, and NoSQL databases (Cassandra, MongoDB, etc.).
• Strong programming skills in Python, Scala, R, or Java, with experience in libraries like Pandas, NumPy, Scikit-learn, TensorFlow, or similar.
• Expertise in statistical analysis, data mining, and predictive analytics techniques.
• Experience working with cloud platforms like AWS, Azure, or Google Cloud for big data processing and analytics.
• Ability to work with large datasets, performing ETL tasks and optimizing data pipelines for speed and efficiency.
• Strong problem-solving and critical thinking skills with the ability to make data-driven decisions in complex business environments.
Set Yourself Apart With:
• Advanced degree (Master’s or PhD) in Data Science, Computer Science, Engineering, or a related field.
• Experience in deploying big data solutions at an enterprise level, particularly in industries like finance, healthcare, or retail.
• Familiarity with containerization technologies (Docker, Kubernetes) for deploying data science solutions.
• Experience with real-time data processing frameworks and stream processing (e.g., Apache Kafka, Apache Flink).
• Knowledge of business intelligence (BI) tools and the ability to present data insights to non-technical stakeholders.
Your Impact:
Lead the development and implementation of scalable big data solutions and advanced analytics frameworks for clients.
• Work closely with cross-functional teams to define business requirements and translate them into actionable data strategies.
• Design and optimize data models and algorithms that solve complex business challenges using large-scale datasets.
• Leverage big data technologies such as Hadoop, Spark, and NoSQL databases to process and analyze large datasets.
• Build and deploy machine learning models that can be integrated into production environments to deliver real-time insights.
• Conduct advanced statistical analysis and predictive modeling to uncover trends, patterns, and opportunities within big data.
• Continuously improve data science processes, ensuring they are efficient, scalable, and aligned with business objectives.
Skills & Experience:
8+ years of experience in data science, big data engineering, or a similar field, with a strong understanding of analytics and machine learning.
• Proficiency with big data technologies such as Hadoop, Spark, Hive, and NoSQL databases (Cassandra, MongoDB, etc.).
• Strong programming skills in Python, Scala, R, or Java, with experience in libraries like Pandas, NumPy, Scikit-learn, TensorFlow, or similar.
• Expertise in statistical analysis, data mining, and predictive analytics techniques.
• Experience working with cloud platforms like AWS, Azure, or Google Cloud for big data processing and analytics.
• Ability to work with large datasets, performing ETL tasks and optimizing data pipelines for speed and efficiency.
• Strong problem-solving and critical thinking skills with the ability to make data-driven decisions in complex business environments.
Set Yourself Apart With:
• Advanced degree (Master’s or PhD) in Data Science, Computer Science, Engineering, or a related field.
• Experience in deploying big data solutions at an enterprise level, particularly in industries like finance, healthcare, or retail.
• Familiarity with containerization technologies (Docker, Kubernetes) for deploying data science solutions.
• Experience with real-time data processing frameworks and stream processing (e.g., Apache Kafka, Apache Flink).
• Knowledge of business intelligence (BI) tools and the ability to present data insights to non-technical stakeholders.
