Overview
On Site
Depends on Experience
Contract - Independent
Contract - W2
Contract - 12 Month(s)
Skills
Communication
Amazon Web Services
Artificial intelligence
Bioinformatics
Cloud computing
Machine Learning (ML)
Machine Learning Operations (ML Ops)
Management
Mathematics
Optimization
Pharmaceuticals
Physics
Python
Quality control
Software deployment
Biology
Computer science
Data Science
Data engineering
Databricks
GitHub
Statistics
Strategy
Testing
Version control
Job Details
Key Responsibilities:
- Development and Testing experience with Data Science Models.
- End-to-end model and pipeline support while producing reusable solutions for scalable use across multiple brands
- Migration of machine learning models, pipelines, python scrips, etc. into MLOps platforms (Dataiku, databricks, MLFlow)
- Deployment of ML solutions for delivery into the field
- Automating model refreshes and pipeline runs with output validation and monitoring
- Developing quality control checks and automated alerts
- Pipeline maintenance, troubleshooting, and documentation
- Pipeline optimization (run-time and stability)
- Delivering reports on model performance, drift, pipeline run times, issue trackers, etc.
Required Qualifications:
- M.S. with 2+ years, or B.S. with 3+ years, of relevant MLOps experience or data engineering experience, in Computer Sciences, Mathematics, Statistics, Machine Learning & Artificial Intelligence, Physics, Engineering, Bioinformatics, Computational Biology or a related discipline
- Experience deploying and operationalizing machine learning models
- Experience creating and enacting strategy for automated model refreshes and pipeline runs, including automated QC checks, tracking model drift, and validating pipeline output
- Experience diagnosing pipeline performance issues or crashes
- Experience with MLOps platforms such as Dataiku, MLFlow, databricks, etc.
- Proficiency in Python and SQL
- Familiarity with PySpark
- Ability to manage and monitor multiple deployed solutions simultaneously
- Proficient with source control platforms such as GitHub or BitBucket
- Experience working with AWS or cloud platforms
- Strong communication skills and ability to communicate complex methods and results to diverse audiences both technical and non-technical
- Understanding of fundamentals underlying common machine learning models
Preferred Qualifications:
- Experience in the commercial pharmaceuticals business
- Experience automating solutions for rapid use across projects
- Experience in pipeline optimization with track record of reducing runtimes
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.