Responsibilities of the Candidate:

• Design and develop advanced statistical, machine learning, and deep learning models to address complex business challenges.
• Fine-tune transformer models to optimize performance for specific tasks and domains.
• Execute ETL processes to clean, transform, and prepare data for analysis and model building.
• Implement ML-Ops practices for seamless model deployment and efficient lifecycle management.
• Analyze large datasets using advanced statistical methods and machine learning techniques.
• Effectively communicate findings and actionable insights to stakeholders.

Requirements:

• Relevant years of experience in data science and machine learning roles
• Strong understanding of data modeling, statistical analysis, and machine learning techniques
• Expertise in Python for application development, including data processing and analysis
• Educational background in fields like Computer Science, IT, Machine Learning, and Data Science
• MLOps certification in AWS or Azure
• Strong proficiency in Python libraries such as NumPy, Pandas, Scikit-learn, and PyTorch
• Extensive experience with deep learning frameworks and techniques
• Hands-on experience fine-tuning transformer models like BERT, GPT, and T5
• Knowledge of database systems (e.g., SQL, NoSQL) with experience in data warehousing and data lake architectures
• Experience with ETL processes and working with data warehouses
• Solid understanding of statistical modeling and machine learning algorithms with practical applications
• Familiarity with MLOps practices and tools such as MLflow, Kubeflow, or similar
• Strong understanding of classification, regression, and graph transformer techniques and their applications
• Experience in root cause analysis and implementing statistical methods for causal inference and experimental design
• Excellent problem-solving, analytical, and critical thinking skills
• Strong communication and collaboration abilities to work effectively in cross-functional teams
• Passionate about staying updated with the latest advancements in data science, machine learning, and related technologies