This job offer is no longer available
About
Our client seeks a Data Science/AI Specialist to build and productionize machine learning solutions, data pipelines, and model deployment workflows. The role will emphasize Python development, SQL, feature engineering, model training, and evaluation with cloud tooling. The specialist will collaborate within agile teams to deliver secure, scalable AI capabilities and support optimization use cases in production.
Applicants must be willing and able to work on a W2 basis. For our W2 consultants, we offer a benefits package that includes Medical, Dental, Vision, 401k with company matching, and life insurance.
Rate: $75.00 to $85.00/hr. W2
Responsibilities
Design, build, and maintain data pipelines for ingestion and transformation using SQL and modern data tooling.
Develop production-quality Python code with clean architecture, testing, and packaging for ML workflows.
Train, evaluate, and tune machine learning models, including feature engineering and model validation.
Apply optimization techniques within ML and analytics workflows to improve outcomes and performance.
Implement CI/CD practices for data and ML services and collaborate on MLOps for model execution pipelines.
Contribute to secure AI architectural patterns and adhere to best practices in cloud environments.
Build and support integrations with data sources such as SQL Server, Oracle, and Hive.
Collaborate within cross-functional agile teams to deliver models and data products to production.
Leverage visualization and statistical analysis to communicate insights and model performance.
Experience Requirements
3 to 4 years of professional experience in data science, machine learning, or related engineering roles.
Strong SQL programming skills, including complex queries and performance considerations.
Production-level Python experience with clean coding, testing, and packaging practices.
Hands‑on experience with TensorFlow, PyTorch, and scikit‑learn for model development.
Experience building data pipelines for ingestion and transformation.
Knowledge of CI/CD pipelines and proficiency in at least one additional programming language.
Understanding of secure AI architectural patterns and agile team practices.
Experience with cloud technologies for ML workflows.
Solid grasp of ML algorithms, optimization, feature engineering, and model evaluation methods.
Experience with data wrangling, statistical analysis, and data visualization libraries.
Basic knowledge of deploying ML models to production.
Familiarity with AWS services for ML workflows such as S3, Lambda, EC2, and SageMaker (preferred).
Prior experience in cross‑functional product teams (preferred).
Experience supporting data scientists to optimize data and model delivery (preferred).
Experience with ETL tools such as SSIS, Sqoop, or Spark (preferred).
Experience with Python and/or PySpark for data processing (preferred).
Expert‑level SQL including joins, CTEs, indexes, stored procedures, and tuning (preferred).
Experience collaborating with MLOps to build pipelines for model execution (preferred).
Experience with data ingestion from SQL Server, Oracle, Hive, and similar sources (preferred).
Experience with architectural and security patterns (preferred).
Knowledge of Docker and MLOps orchestration (preferred).
Education Requirements
Bachelor’s degree in Computer Science, Information Systems, or related discipline, or 8 years of equivalent work experience.
AWS‑related certifications (preferred).
#J-18808-Ljbffr
Languages
- English
Notice for Users
This job was posted by one of our partners. You can view the original job source here.