Senior Data Scientist
sdna global
Dallas, TX, United States
19 days ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Compensation
$124,800.0 - $135,200.0
Working hours
Regular working hours
Job source
Tech stack
Java (Programming Language)
Artificial Intelligence
Amazon Web Services
Data Analysis
Bash Shell
Big Data
Extract Transform Load (ETL)
Data Mining
Database Design
R (Programming Language)
Apache Hadoop
Python (Programming Language)
+16 more
Linked Data
Machine Learning
Natural Language Processing
Cloud Services
Tensorflow
SQL Databases
Data Streaming
Talend
Data Processing
Apache Spark
Model Validation
Generative AI
Deployment Automation
Data Analytics
Data Pipelines
Unsupervised Learning
Job description
- Design, develop, and optimize machine learning models using frameworks such as TensorFlow and other AI tools to solve complex business problems.
- Lead end-to-end data analysis projects, including data extraction, transformation (ETL), and statistical modeling to generate actionable insights.
- Collaborate with cross-functional teams to implement scalable big data systems utilizing Hadoop, Spark, and cloud services like AWS for efficient data processing.
- Develop predictive models for natural language processing, generative AI applications, and other AI-based solutions that enhance product offerings.
- Conduct statistical analysis for research purposes, ensuring rigorous evaluation of model performance through model training, testing, and evaluation metrics.
- Design and maintain robust SQL databases and data pipelines using Talend or Bash scripting to facilitate seamless data flow across platforms.
- Evaluate AI models for accuracy, scalability, and deployment readiness while ensuring compliance with best practices in model evaluation and deployment strategies.
Requirements
- Proven experience in machine learning/AI development with proficiency in Python, R, Java, or C for algorithm implementation.
- Strong background in statistical analysis tools and techniques for research and predictive modeling analysis.
- Hands-on experience with big data systems such as Hadoop, Spark (including Spark implementation), and cloud-based machine learning services like AWS or similar platforms.
- Expertise in database design, SQL databases, ETL processes, and data mining techniques to support large-scale analytics initiatives.
- Familiarity with natural language processing (NLP), generative AI models, and AI implementation strategies for real-world applications.
- Knowledge of statistical modeling methods including unsupervised learning approaches for clustering or anomaly detection tasks.
- Ability to work with diverse datasets such as linked data or big data systems while ensuring scalability and efficiency in model deployment.
- Excellent problem-solving skills combined with strong communication abilities to translate complex technical concepts into actionable insights for stakeholders.
Join us if you’re passionate about harnessing the power of data analytics and AI to revolutionize industries! We value innovation, collaboration, and a proactive mindset-your expertise will be instrumental in shaping our technological future.
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