Hypothesis Testing, T-Test, Z-Test, Regression (Linear, Logistic), Python/PySpark, SAS/SPSS, Statistical analysis and computing, Probabilistic Graph Models, Great Expectation, Evidently AI, Forecasting (Exponential Smoothing, ARIMA, ARIMAX), Tools(KubeFlow, BentoML), Classification (Decision Trees, SVM), ML Frameworks (TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, MXNet), Distance (Hamming Distance, Euclidean Distance, Manhattan Distance), R/ R Studio
Job requirements
Key Responsibilities - Develop and optimize machine learning models for various applications. - Implement AI algorithms, including deep learning, neural networks, and natural language processing (NLP). - Design and maintain data pipelines for model training and deployment. - Collaborate with cross-functional teams to integrate AI solutions into products. - Conduct research on emerging AI technologies and best practices. - Ensure scalability, reliability, and efficiency of AI models in production environments. - Troubleshoot and improve existing AI/ML systems. Required Skills & Qualifications - Experience: 3-8 years in AI/ML development. - Technical Skills: Proficiency in Python, TensorFlow, PyTorch, and other ML frameworks. - Data Handling: Strong knowledge of data preprocessing, feature engineering, and model evaluation. - Cloud & Deployment: Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes). - Problem-Solving: Ability to analyze complex problems and develop AI-driven solutions.
