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).