Senior Data Scientist

MAES Solutions is seeking a Data Scientist to develop and implement machine learning, statistical modeling, predictive analytics, and AI solutions. The role focuses on building and deploying models, developing end-to-end data science workflows, and communicating insights to business stakeholders.

Responsibilities

• Develop, train, validate, and deploy machine learning models for classification, regression, clustering, forecasting, recommendation, anomaly detection, and predictive analytics use cases
• Perform exploratory data analysis (EDA) , statistical analysis, data profiling, data preprocessing, data cleansing, and feature engineering to identify meaningful patterns and business insights
• Build predictive models using Python, Scikit-learn, Pandas, NumPy, XGBoost, LightGBM, and other machine learning frameworks
• Apply advanced statistical modeling, hypothesis testing, regression analysis, probability, time-series analysis, correlation analysis, and experimental design to solve complex business problems
• Develop and optimize Deep Learning models using frameworks such as T ensorFlow, PyTorch, Keras, and related AI/ML technologies
• Design and implement Natural Language Processing (NLP) solutions for text classification, sentiment analysis, document processing, information extraction, text summarization, and semantic analysis
• Work with Generative AI, Large Language Models (LLMs), embeddings, vector databases, prompt engineering, Retrieval-Augmented Generation (RAG), and AI-powered applications where applicable
• Develop end-to-end data science solutions, from data collection and preprocessing through model development, evaluation, deployment, monitoring, and continuous improvement
• Evaluate model performance using appropriate evaluation metrics, cross-validation, hyperparameter tuning, model selection, explainability, and statistical validation techniques
• Implement MLOps practices model versioning, experiment tracking, deployment automation, model monitoring, drift detection, and lifecycle management
• Work with cloud-based AI/ML platforms such as Microsoft Azure, Azure Machine Learning, Azure Databricks, Azure Data Lake, and Azure Synapse Analytics
• Develop scalable data processing and machine learning workflows using Apache Spark, PySpark, Databricks, and distributed computing technologies
• Create dashboards, visualizations, and analytical reports using Power BI, Tableau, Matplotlib, Seaborn, or other visualization tools to communicate insights to business stakeholders

Skills

• 8+ years of experience in Data Science, Machine Learning, Predictive Analytics, Statistical Modeling, and Advanced Analytics
• Strong programming expertise in Python, with hands-on experience using Pandas, NumPy, Scikit-learn, SciPy, Matplotlib , and Seaborn
• Extensive knowledge of Machine Learning algorithms , including Linear/Logistic Regression, Decision Trees, Random Forest, Gradient Boosting, XGBoost, LightGBM, SVM, K-Means, Clustering, PCA, and Ensemble Methods
• Hands-on experience with Deep Learning frameworks such as TensorFlow, PyTorch, and Keras, including neural networks and model optimization
• Experience with Natural Language Processing (NLP), including text classification, sentiment analysis, tokenization, embeddings, transformers, and language models
• Strong understanding of Generative AI, Large Language Models (LLMs), Prompt Engineering, RAG, Vector Databases, Embeddings, and AI application development

Company Overview

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