We are hiring for our client in the biotechnology industry.
Duration: 6 months (extendable)
100% onsite.
Responsibilities:
Collaborate with stakeholders to understand data requirements for machine learning, data science, and analytics projects.
Assemble large, complex data sets from disparate sources, writing code, scripts, and queries to efficiently extract, quality check, clean, harmonize, and visualize Big Data sets.
Write pipelines for optimal extraction, transformation, and loading of data from a wide variety of sources using Python, SQL, Spark, and AWS big data technologies.
Develop and design data schemas to support data science team development needs.
Identify, design, and implement continuous process improvements, such as automating manual processes and optimizing data delivery.
Design, develop, and maintain a dedicated machine learning inference pipeline on the AWS platform using SageMaker, EC2, and related services.
Deploy inference pipelines on dedicated EC2 instances or Amazon SageMaker.
Establish data pipelines to store and maintain inference output results, tracking model performance and key performance indicators (KPIs).
Document data processes, write recommended procedures, and create training materials related to data management best practices.
Requirements:
Bachelor's or Master's degree in Computer Science, Computer Engineering, or equivalent experience.
5-7 years of experience developing and deploying data and machine learning pipelines.
5 years of experience deploying machine learning models via AWS SageMaker and AWS Bedrock.
Proficiency in programming and scripting with Python, SQL, and Spark.
Deep knowledge of AWS core services, including RDS, S3, API Gateway, EC2/ECS, Lambda, and more.
Hands-on experience with model monitoring, drift detection, and automated retraining processes.
Experience with CI/CD pipeline implementation using tools such as GitHub (Workflows and Actions), Docker, Kubernetes, Jenkins, and Blue Ocean.
Familiarity with Agile/Scrum-based software development structures.
5 years of experience with data visualization and/or API development for data science users.