Key Responsibilities:Â

• Design and implement robust data pipelines to collect, clean, and process large volumes of structured and unstructured data.Â
• Optimize data workflows and machine learning systems to ensure efficiency and reliability.Â
• Work closely with data analysts, data scientists, and stakeholders to define data requirements and deliver actionable insights.Â
• Contribute on AI projects using RAG and LLM.Â
• Perform exploratory data analysis and contribute to the creation of predictive and prescriptive analytics.Â
• Stay updated with the latest trends in data science, machine learning, and big data technologies.Â

Qualifications:Â

• Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, or a related field.Â
• Proficiency in programming languages such as Python, R, or Scala.Â
• Strong experience with big data tools and frameworks (e.g., Spark, Databricks) and cloud platforms (e.g., AWS, Azure, Google Cloud).Â
• Solid understanding of machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn).Â
• Hands-on experience with SQL and NoSQL databases.Â
• Knowledge of CI/CD pipelines and MLOps principles.Â
• Excellent problem-solving skills and a keen eye for detail.Â
• Strong communication skills and the ability to work collaboratively in a team environment.Â

Preferred Skills:Â

• Familiarity with advanced analytics techniques (e.g., NLP, computer vision).Â
• Experience in software development practices and version control systems (e.g., Git).Â
• Knowledge of data visualization tools (e.g., Power BI).Â