Data Scientist with Statistics Skills

As a Machine Learning Engineer at our company, you will be responsible for SAS to Python code conversion, acquiring skills for building machine learning models, and deploying them for production. Your role will involve feature engineering, exploratory data analysis, pipeline creation, model training, and hyperparameter tuning with both structured and unstructured datasets. Additionally, you will develop and deploy cloud-based applications, including LLM/GenAI, into production. Key Responsibilities: - Hands-on experience working with SAS to Python conversions - Strong mathematics and statistics skills - Skilled in AI-specific utilities like ChatGPT, Hugging Face Transformers, etc - Ability to understand business requirements - Use case derivation and solution creation from structured/unstructured data - Storytelling, Business Communication, and Documentation - Programming Skills in SAS, Python, Scikit-Learn, TensorFlow, PyTorch, Keras - Exploratory Data Analysis - Machine Learning and Deep Learning Algorithms - Model building, Hyperparameter tuning, and Model performance metrics - MLOps, Data Pipeline, Data Engineering - Statistics Knowledge including Probability Distributions, Hypothesis Testing - Time series modeling, Forecasting, Image/Video Analytics, and Natural Language Processing (NLP) - ML services from Clouds such as AWS, GCP, Azure, and Databricks - Optional - Databricks, Big Data -Basic knowledge of Spark, Hive Qualifications: - 7 to 10 years of experience - Skills Required: Python, SAS, Machine Learning In this role, you will utilize your expertise in SAS to Python conversions, machine learning algorithms, and cloud-based applications to drive innovative solutions and contribute to the success of our team.,