Offer summary

Qualifications:

8+ years of IT experience, Strong skills in Python, Machine Learning on Azure, SQL, and MLOps, Understanding of statistical analysis and modeling techniques, Experience in deploying and monitoring machine learning models..

Key responsibilities:

Develop and implement machine learning models for business solutions

Deploy and monitor models in production environments

Maintain and update machine learning models over time

Create documentation and participate in asset demos for data science assets.

Job description

Job Description

Must have Skills : Python (Strong), Machine Learning on Azure (Strong), SQL (Strong), Model Deployment and Monitoring (Strong), MLOps,

Job Description :

Must have 8+ years of IT experience.
Develop and implement machine learning models to solve complex business problems.
Strong understanding of statistical analysis and modelling techniques (e.g., regression analysis, hypothesis testing, time series analysis)
Deploy machine learning models to production environments, ensuring that models are integrated with software systems.
Monitor machine learning models in production, ensuring that models are performing as expected and that any errors or performance issues are identified and resolved quickly.
Maintain machine learning models over time. This includes updating models as new data becomes available, retraining models to improve performance, and retiring models that are no longer effective.
Develop and implement policies and procedures to ensure the ethical and responsible use of machine learning models. This includes addressing issues related to bias, fairness, transparency, and accountability.
Design, contribute, and participate in the implementation of Python libraries answering a data science transversal need that can be reused in several projects.
Maintain existing data science assets (timeseries forecasting asset, model monitoring asset)
Create documentation and knowledge based on data science assets to ensure users understand them well.
Participate in asset demos to showcase new features to users.
Proactively identify areas of improvement within the pipelines.
Must have experience in MLOps.
Good to have knowledge of Deep Learning fundamentals.

Required profile