- Design, build, and test machine learning model monitoring capabilities with the highest standard.
- Create new model evaluation and analysis tools.
- Build/Incorporate ML models and navigate them through the entire ML model development life-cycle.
- Implement prototype and product grade code for solutions.Design and Build CI/CD and ML/Data ops dev pipeline
- Master’s or Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field.
- Experience in programming: Preferred - Scala & Python, Java/GO
- Knowledge and experience in one of these fields:
- Applying various machine learning(ML) techniques, and understanding the key parameters that affect their performance. Knowledge in building & re-engineering supervised/un-supervised and ensemble models on structured and semi-structured data.
- Developing experimental and analytic plans for model & data modeling processes, use of strong baselines, and the ability to accurately determine cause and effect relationships.
- Any of these products Python or SAS or R
- ML Frameworks (One or more): MLFlow, PyTorch, TensorFlow
- Building ML models with any one cloud platform (GCP, Azure, AWS).
- Excited to tackle difficult research questions.
- Problem solver who can work both individually as well as in a team.
- Hands on experience leading large-scale global adv.analytics & DataOps/MLOPs projects
- Proven experience in programming like open source contributions, publications or patents.
But “Digital Transformation” is an empty buzz phrase without a culture that allows for innovation, creativity, and yes, even failure (if you learn from it.)