Data Scientist

Role Overview

The Data Scientist will be responsible for creating scalable machine learning solutions and AI-driven applications that solve intricate business problems and improve decision-making processes.

Main Duties

• Handle extensive and intricate datasets to address difficult business challenges.
• Gather, clean, and preprocess data to prepare for analysis and model training effectively.
• Conduct exploratory data analysis (EDA) to extract meaningful insights and guide model creation.
• Design, train, and fine-tune machine learning models leveraging advanced algorithms and frameworks.
• Construct full ML pipelines covering data ingestion, preparation, model development, validation, and deployment.
• Automate training, testing, and deployment processes through CI/CD pipelines alongside MLOps practices.
• Work collaboratively with various teams to embed models into software applications for comprehensive solutions.

Qualifications and Experience

• A minimum of five years' experience in data science, machine learning, or artificial intelligence domains.
• Comprehensive knowledge in supervised and unsupervised learning, deep learning techniques, natural language processing, computer vision, or generative AI such as large language models.
• Proficient programming skills in Python and/or R along with SQL capabilities for data extraction.
• Experience in constructing data pipelines using technologies like Spark, Airflow, and Hadoop, including working with big data ecosystems.
• Familiarity with model deployment concepts, API development using frameworks like FastAPI or Flask, and optimizing models for real-time or batch inference.
• Competence in containerization and orchestration tools including Docker and Kubernetes; use of CI/CD tools and MLOps platforms like MLflow or Kubeflow.
• Hands-on deployment experience on cloud platforms such as AWS, Google Cloud, or Azure using services like Sagemaker or Vertex AI.
• Possess a Master’s degree in Computer Science or a related discipline.