Data Scientist

Responsibilities

• Work with large and complex data sets to solve challenging business problems
• Collect, clean, and preprocess large datasets for analysis & model training
• Perform exploratory data analysis (EDA) to uncover insights and inform model development
• Develop, train, and optimize machine learning models using state‑of‑the‑art algorithms and frameworks
• Build end‑to‑end ML pipelines, including data ingestion, transformation, model training, validation, and deployment
• Automate workflows for model training, testing, and deployment using CI/CD pipelines and MLOps tools
• Collaborate with cross‑functional teams to integrate models into applications and deliver end‑to‑end solutions

• 5+ years of experience in data science, machine learning, or AI
• Expertise in supervised/unsupervised learning, deep learning, NLP, computer vision, or generative AI (e.g., LLMs).
• Strong proficiency in Python and/or R; familiarity with SQL for data querying
• Ability to build data pipelines (Spark, Airflow, Hadoop) and work with big data tools
• Understanding of model serving, API development (FastAPI, Flask), and optimizing model performance for real‑time or batch inference
• Knowledge of Docker, Kubernetes, CI/CD pipelines, and tools like MLflow/Kubeflow for model lifecycle management (MLOps)
• Experience deploying models on AWS, Google Cloud, Azure, or similar (e.g., Sage Maker, Vertex AI)
• Educational qualifications:
  Bachelor’s degree in Computer Science, Engineering, or related field required