Data Scientist

We are seeking a skilled Machine Learning Engineer / Data Scientist with 5+ years of experience to design, develop, and deploy scalable machine learning models. The ideal candidate will have strong expertise in data analysis, feature engineering, and building traditional ML models, along with hands‑on experience in Python-based data science tools. Key Responsibilities 1.

Data Engineering Collaboration Collaborate with data engineering teams to support and optimize ETL processes Work with large-scale structured and unstructured datasets 2. Exploratory Data Analysis (EDA) Perform data cleaning, transformation, and manipulation Conduct exploratory data analysis using tools such as Pandas, NumPy, and SciPy Generate insights and identify patterns to support model development Build and implement traditional machine learning models (non-GenAI/LLM/NLP) Focus on: Classification (primary focus) Regression Select appropriate algorithms and optimize model performance Validate model performance using appropriate metrics and techniques Ensure robustness, scalability, and accuracy of models Perform cross‑validation and error analysis 5. Documentation Prepare comprehensive documentation for models, methodologies, and processes Maintain clear records for reproducibility and knowledge sharing Work closely with MLOps teams to deploy models into production Support monitoring, maintenance, and performance tuning of deployed models Required Skills Machine Learning: Strong understanding of supervised and unsupervised learning techniques Programming: Python for Data Science Data Analysis Tools: Pandas, NumPy, SciPy Database: MySQL Data Handling: Data preprocessing, feature engineering, and model evaluation Preferred Qualifications Experience working with production ML pipelines Familiarity with model deployment and monitoring frameworks Strong problem‑solving and analytical skills #J-18808-Ljbffr