AWS Data Scientist

Smart Caliber Technology
Malvern, PA, United States
about 2 months ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
8 years minimum
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Amazon Web Services Amazon Elastic Compute Cloud Amazon S3 Business Analytics Applications Data Analysis Big Data Cloud Engineering Computer Programming Data Security Data Visualization Python (Programming Language)
+16 more
Machine Learning NumPy Tensorflow SQL Databases Data Streaming Feature Engineering Pytorch Apache Spark Deep Learning Pandas Build Management Scikit Learn AWS Data Analytics Machine Learning Operations Software Version Control Unsupervised Learning

Job description

  • Design, develop, and deploy AI/ML models and data science solutions on AWS
  • Build end-to-end ML pipelines using AWS services such as SageMaker, Lambda, EC2, and ECR
  • Perform advanced data analysis, feature engineering, model training, and optimization using Python
  • Work with large-scale datasets using AWS data services including S3, Glue, Athena, and Redshift
  • Implement MLOps practices for model deployment, monitoring, retraining, and version control
  • Translate complex business problems into AI/ML-driven solutions
  • Ensure adherence to data security, governance, and compliance standards

Requirements

We are looking for a highly experienced AWS Data Scientist with deep expertise in Artificial Intelligence (AI), Machine Learning (ML), and advanced Python programming to build and deploy scalable, cloud-native analytics solutions on AWS. The role requires hands-on experience across the full data science lifecycle and close collaboration with business and engineering teams., * Minimum 8+ years of experience in Data Science, AI, or Machine Learning

  • Strong hands-on expertise in AI & ML, including supervised and unsupervised learning, NLP, or deep learning
  • Advanced Python programming skills, including libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch
  • Extensive experience with AWS, especially SageMaker, S3, Redshift, Glue, Athena, Lambda
  • Strong foundation in statistics, predictive modeling, and ML algorithms
  • Proficiency in SQL and experience with data visualization techniques
  • Excellent communication and stakeholder management skills, * AWS Certifications (Machine Learning - Specialty or Solutions Architect)
  • Experience with big data technologies such as Spark
  • Exposure to real-time or streaming data pipelines
  • Background in financial services or regulated industries

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