Key Responsibilities:

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

Qualifications:

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

Preferred Skills:

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