• 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.)