What are the responsibilities and job description for the AI/ML Data Scientist - Python, MLOps, Quantitative, Statistics position at Jobs via Dice?
Dice is the leading career destination for tech experts at every stage of their careers. Our client, SES, is seeking the following. Apply via Dice today!
Top 5 Technical Skills:
We are seeking a Full Stack Data Scientist to develop AI/ML solutions end-to-end, from business problem formulation and model development through production-ready application delivery and operationalization. This role combines deep modeling expertise, strong software engineering skills, and practical MLOps experience. The ideal candidate builds models that matter, writes code that lasts, and partners with platform teams to deploy, monitor, and operate AI/ML solutions efficiently and reliably at scale.
Key Responsibilities
Translate complex business requirements into AI/ML-based technical solutions and ensure efficiency, scalability and reliability
Design, develop, validate, and document AI/ML models and applications
Build production-grade Python code and pipelines for data processing, feature engineering, training, and inference.
Develop model-driven applications and services (batch or real-time).
Apply software engineering best practices including modular design, testing, code reviews, and CI/CD.
Collaborate with MLOps teams on deployment, monitoring, versioning, and retraining.
Implement model performance, stability, and data drift monitoring.
Produce documentation to support governance, validation, and audit requirements.
Required Qualifications:
Proven hands-on experience (6 years preferred) in production-ready models and applications that solve real business problems while actively participating in MLOps to ensure solutions operate reliably in production.
Strong experience in statistical modeling, machine learning, AI, and applied analytics.
Advanced proficiency in Python, ML libraries, SQL, and big data processing (e.g. pandas, NumPy, scikit-learn, TensorFlow, PySpark ).
Experience writing production-ready, maintainable code and application design.
Strong experience with AWS cloud ML platforms (e.g., AWS SageMaker, MLFlow, S3, compute services, Redshift).
Experience with model deployment and MLOps practices
Strong problem-solving and communication skills.
Education Bachelor s or Master s degree in Data Science, Statistics, Computer Science, Engineering, or a related quantitative field.
About SES:
Systems Engineering Services Corporation (SESC), founded in 1989, is a leading provider of technology solutions to Fortune 1000 companies and government organizations. Specializing in Accelerated Development Services (agile application development, mobile, systems integration, project and program management), Architecture Services (SOA, microservices, Cloud), Data Services (DW, BI, Big Data), Testing, Cyber Security and DevOps, SESC is guided by a corporate mission to provide valuable solutions to our client s technology needs through responsive quality services.
Contact Information:
Please contact me for all of the details of the client company, environment, and the position. I look forward to speaking with you.
Jim Murphy
Top 5 Technical Skills:
- Statistical modeling, machine learning, AI, and applied analytics
- Python
- AWS ML Platforms (AWS SageMaker, MLFlow, S3, compute services, Redshift)
- Model deployment and MLOps practices
- Data Processing
We are seeking a Full Stack Data Scientist to develop AI/ML solutions end-to-end, from business problem formulation and model development through production-ready application delivery and operationalization. This role combines deep modeling expertise, strong software engineering skills, and practical MLOps experience. The ideal candidate builds models that matter, writes code that lasts, and partners with platform teams to deploy, monitor, and operate AI/ML solutions efficiently and reliably at scale.
Key Responsibilities
Translate complex business requirements into AI/ML-based technical solutions and ensure efficiency, scalability and reliability
Design, develop, validate, and document AI/ML models and applications
Build production-grade Python code and pipelines for data processing, feature engineering, training, and inference.
Develop model-driven applications and services (batch or real-time).
Apply software engineering best practices including modular design, testing, code reviews, and CI/CD.
Collaborate with MLOps teams on deployment, monitoring, versioning, and retraining.
Implement model performance, stability, and data drift monitoring.
Produce documentation to support governance, validation, and audit requirements.
Required Qualifications:
Proven hands-on experience (6 years preferred) in production-ready models and applications that solve real business problems while actively participating in MLOps to ensure solutions operate reliably in production.
Strong experience in statistical modeling, machine learning, AI, and applied analytics.
Advanced proficiency in Python, ML libraries, SQL, and big data processing (e.g. pandas, NumPy, scikit-learn, TensorFlow, PySpark ).
Experience writing production-ready, maintainable code and application design.
Strong experience with AWS cloud ML platforms (e.g., AWS SageMaker, MLFlow, S3, compute services, Redshift).
Experience with model deployment and MLOps practices
Strong problem-solving and communication skills.
Education Bachelor s or Master s degree in Data Science, Statistics, Computer Science, Engineering, or a related quantitative field.
About SES:
Systems Engineering Services Corporation (SESC), founded in 1989, is a leading provider of technology solutions to Fortune 1000 companies and government organizations. Specializing in Accelerated Development Services (agile application development, mobile, systems integration, project and program management), Architecture Services (SOA, microservices, Cloud), Data Services (DW, BI, Big Data), Testing, Cyber Security and DevOps, SESC is guided by a corporate mission to provide valuable solutions to our client s technology needs through responsive quality services.
Contact Information:
Please contact me for all of the details of the client company, environment, and the position. I look forward to speaking with you.
Jim Murphy