Lead Data Scientist

Responsibilities:

1. Leadership and Team Management:
   Lead and manage a team of data scientists and machine learning engineers.
   Provide mentorship and guidance to junior team members, fostering a collaborative and innovative environment.
2. Machine Learning and AI Development:
   Develop and implement advanced machine learning models using Azure ML.
   Conduct time series analysis to forecast and analyze trends.
   Design and deploy deep learning models for various applications.
   Explore and implement generative AI techniques to solve complex problems.
   Build end-to-end AI/ML solutions on cloud platforms, particularly Azure.
   Utilize Azure cloud services such as Azure Databricks, Data Factory, Synapse Analytics, and Cognitive Services.
   Apply skills in NLP, Computer Vision, and Large Language Models (LLMs).
   Implement a variety of machine learning algorithms, including but not limited to:
   
   • Linear and Non-Linear Regression models
   • Decision Trees and Random Forests
   • Gradient Boosting Machines (GBM)
   • Support Vector Machines (SVM)
   • K-Nearest Neighbors (KNN)
   • Clustering algorithms (K-Means, Hierarchical Clustering)
3. Continuous Improvement:
   Skills on MLOps
   Continuously monitor and improve model performance and accuracy.
   Stay updated with the latest advancements in AI/ML and cloud technologies.
   Demonstrate dynamic and enthusiastic learning of new technologies.

Requirements:

1. Proven experience as a Lead Data Scientist or similar role.
2. Strong expertise in machine learning, with a focus on Azure ML.
3. Extensive experience in time series analysis and forecasting.
4. Proficiency in deep learning frameworks such as TensorFlow or PyTorch.
5. Knowledge of generative AI techniques and applications.
6. Demonstrated experience in building end-to-end AI/ML solutions on cloud platforms, especially Azure.
7. Experience with Azure cloud services like Azure Databricks, Data Factory, Synapse Analytics, and Cognitive Services.
8. Strong experience in natural language processing (NLP), including techniques and applications.
9. Skills in Computer Vision and Large Language Models (LLMs).
10. Strong programming skills in Python and R.
11. Excellent problem-solving skills and ability to think critically.
12. Strong project management skills, with experience in leading and delivering complex projects.
13. Exceptional communication skills, both written and verbal, with the ability to convey technical information to a diverse audience.
14. Proven record of building and leading data science/AI/ML projects end-to-end.
15. Strong statistical and mathematical knowledge.