Data Scientist
3 weeks ago
At Lilly, we are committed to discovering and developing innovative medicines to improve human health.
The LCCI Business Insights & Analytics team is seeking a talented Machine Learning Engineer to join our team.
This role will be an integral part of the ML Ops pillar within BI&A, responsible for managing projects requiring ML Ops expertise across the commercial analytics continuum.
Key Responsibilities:
- Creation and automation of ML Ops pipelines on cloud and premise, CI/CD pipelines orchestration across multiple projects
- ML models code refactoring, training, retraining, deployment, testing and continuous monitoring for drift
- Applying software engineering rigor and best practices to machine learning, including CI/CD, automation, etc
- Optimisation of model hyper parameters
- Evaluation and explicability of models
- Model onboarding, operations, and decommissioning workflows
- Creating and maintaining scalable MLOps frameworks to support client-specific models
- As MLOps expert, providing technical design solutions to support PoVs
- Measure and improve services, create and use benchmarks, metrics, and monitoring
- Providing best practises and running proof-of-concepts for automated and efficient model operations on a large scale
- Coordinate with diverse stakeholders such as statisticians, software engineers, infrastructure teams to better understand requirements and constraints to design the most optimal ML pipelines
Requirements:
- 4-8 years of demonstrated expertise in building ML/automation pipelines from scratch (Including model versioning, model and data lineage, monitoring, model hosting and deployment, model optimization, scalability, orchestration, continuous learning, Automated pipelines)
- Proficient in AWS components such as Sage maker, AWS Lambda, other AWS services, serverless services, etc
- Strong knowledge of python and PySpark. Working knowledge of R is preferred
- Strong knowledge of working tools like Docker, Kubernetes, Jenkins
- Experience in using popular MLOps frameworks like Kubeflow, MLFlow, and DataRobot
- Knowledge of frameworks such as scikit-learn, Keras, PyTorch, Tensorflow, etc. and ability to understand tools used by data scientist
- Some Hands -on the table's creations, DDL, DML and TCL
- Experience with AWS cloud services: EC2, EMR, RDS, Redshift, S3, Athena is ad advantage
- Experience with data pipeline and workflow management tools: Airflow etc
- Experience developing new components in a scrum/agile environment
- Excellent verbal and written communication skills with the ability to effectively advocate technical solutions to data scientists, engineering teams and business audiences
Education:
Bachelor's or Master's in Computer Applications/Computer Science OR Specialization/courses in ML/DS, having deep understanding of SDLC.
Lilly does not discriminate on the basis of age, race, color, religion, gender, sexual orientation, gender identity, gender expression, national origin, protected veteran status, disability or any other legally protected status.
#WeAreLilly
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