Freelance Senior Data Scientist – Machine Learning & MLOps

About the Role
We are looking for an experienced Senior Data Scientist with strong expertise in Machine Learning, MLOps, and time series forecasting. The ideal candidate should have hands-on experience building, deploying, tracking, and optimizing machine learning models using Python, MLflow, Databricks, and Azure cloud technologies.
This is a part-time, fully remote opportunity for professionals who can deliver scalable, reliable, and data-driven ML solutions.
Key Responsibilities
Develop, train, evaluate, and optimize machine learning models using Python.
Build predictive models using XGBoost, Decision Trees, and other supervised learning algorithms.
Develop LSTM-based models and implement time series forecasting solutions.
Implement MLOps workflows for experiment tracking, model versioning, deployment, and monitoring using MLflow.
Work with Databricks for large-scale data processing, model development, and experimentation.
Write efficient SQL queries for data extraction, transformation, and analysis.
Integrate machine learning workflows with Azure Data Lake and Azure DevOps CI/CD pipelines.
Monitor model performance, detect data/model drift, and improve model reliability.
Collaborate with stakeholders to translate business requirements into practical ML solutions.
Required Skills
Strong hands-on experience in Machine Learning and Predictive Analytics.
Advanced Python programming and SQL skills.
Practical experience with MLOps and MLflow.
Expertise in XGBoost, Decision Trees, and model evaluation techniques.
Experience with LSTM networks and time series forecasting.
Working knowledge of Databricks and distributed data processing.
Experience with Azure Data Lake and Azure DevOps.
Understanding of model deployment, monitoring, versioning, and CI/CD practices.
Preferred Qualifications
Experience deploying production-grade machine learning solutions.
Familiarity with cloud-based ML pipelines and automated model retraining.
Strong analytical, problem-solving, and communication skills.
Opportunity Details
Part-time, fully remote engagement.
Contract-based opportunity.
Flexible working arrangement with agreed deliverables and timelines.
Interested candidates: Apply through LinkedIn with your updated resume highlighting relevant Machine Learning, MLOps, and forecasting experience.

Work arrangement
Yes