Data Scientist with Machine Learning specialization:

Key Responsibilities Design, develop, and deploy machine learning models for prediction, recommendation, anomaly detection, NLP, or image processing tasks. Work with large, complex datasets to extract insights and build scalable solutions. Collaborate with data engineers to create efficient data pipelines and feature engineering workflows. Evaluate model performance using appropriate metrics and improve models through iterative testing and tuning. Communicate findings, insights, and model outputs clearly to non-technical stakeholders. Stay up to date with the latest machine learning research, frameworks, and technologies. Required Skills Strong programming skills in Python (Pandas, NumPy, Scikit-learn, etc.). Hands-on experience with ML/DL frameworks like TensorFlow, PyTorch, XGBoost, or LightGBM. Experience in building, deploying, and maintaining end-to-end ML models in production. Solid understanding of statistics, probability, and mathematical modeling. Proficiency with SQL and data manipulation in large-scale databases. Familiarity with version control (Git), CI/CD workflows, and model tracking tools (MLflow, DVC, etc.). Preferred Skills Experience with cloud platforms like AWS, GCP, or Azure (e.g., SageMaker, Vertex AI). Knowledge of MLOps practices and tools for scalable ML deployments. Exposure to real-time data processing or streaming (Kafka, Spark). Experience with NLP, Computer Vision, or Time Series Forecasting. Show more Show less