Data Scientist

Job highlights

• Proficiency with Python,SQL,and ML frameworks (TensorFlow,PyTorch,Scikit-learn,etc.)

• Strong experience in Data Engineering (ETL pipelines,data warehousing,distributed systems)

• Hands-on experience with cloud platforms (AWS,GCP,Azure) and big data technologies (Spark,Kafka,Databricks)

• Experience with LLMs,prompt engineering,and generative AI

• Lead the design, development, and deployment of machine learning models for real-world business problems.

• Drive end-to-end data pipelines, from data ingestion and transformation to model serving and monitoring.

• Collaborate with cross-functional teams to define data strategies, ensuring high-quality, reliable data for analytics and ML use cases.

• Mentor junior data scientists and engineers, setting best practices in modeling, MLOps, and data engineering.

• Explore and evaluate emerging trends in Agentic AI and advanced ML techniques to incorporate into future product capabilities.

• Work closely with product and engineering leadership to align data initiatives with business goals.

The Perfect Fit

• Proven expertise in Data Science & Machine Learning (model development, deployment, and scaling).
• Strong experience in Data Engineering (ETL pipelines, data warehousing, distributed systems).
• Proficiency with Python, SQL, and ML frameworks (TensorFlow, PyTorch, Scikit-learn, etc.).
• Hands-on experience with cloud platforms (AWS, GCP, Azure) and big data technologies (Spark, Kafka, Databricks).
• Solid understanding of MLOps practices (CI/CD for ML, model monitoring, reproducibility).
• Excellent problem-solving, communication, and leadership skills.

Your Edge Over the Rest

• Exposure to Agentic AI frameworks and research in autonomous AI systems.
• Experience with LLMs, prompt engineering, and generative AI.
• Knowledge of advanced optimization and reinforcement learning.