Position: Data Science Engineer Data
Basic Qualifications
- Bachelor's or master's degree in computer science, IT or related technical field
- 5+ years of professional software development experience
- 3+ year experience with programming languages such as Python, R and open-source technologies (Apache, Hadoop, Spark, PyTorch, TensorFlow)
Preferred Qualifications
- Proficiency in Python, R, Spark.
- Machine learning knowledge and experience.
- Experience building tools for data scientists and developers. Must have experience in AWS SageMaker and AWS SageMaker Studio
- Experience with IDE/notebook software (Jupyter Studio, R-Studio, VSCode, PyCharm, etc)
- Experience in building data pipeline using on cloud using Cloud technologies (S3, Lakeformation, SQS, SNS, Kinesis, Spark, Kafka, Glue etc)
- Good to have experience in Data Visualization tools like SAS, Tableau, AWS Quicksight
Key Responsibilities:
- Design and implement cloud solutions, build MLOps on cloud. Preferably AWS Cloud.
- Build model and data pipelines for Data Scientists and Data Engineers using AWS cloud services.
- Assist in data science model review, run the code refactoring and optimization, containerization, deployment, versioning, and monitoring of its model quality.
- Hands on experience with different features of AWS SageMaker including but not limited to SageMaker Studio, Jupyter Notebooks, Data Wrangler, Clarify etc.
- Good understanding of the Python ML Libraries. Should be able to prototype and evaluate new libraries and new features available.
- Experience in communicating with Data science team, Cloud Infrastructure team and developers to collect requirements, describe software product features, and technical designs.
- Ability and willingness to multi-task and learn new technologies quickly
- Stakeholder management with good Written and verbal technical communication skills with an ability to present complex technical information in a clear and concise manner to a variety of audiences
