Data Scientist

Job Title: Data Scientist Location : Richardson, TX (5 days onsite) Role Type : Contract Job Summary: We are seeking a highly skilled Data Scientist to join our analytics and AI team. The ideal candidate will have strong expertise in statistical modeling, machine learning, NLP, forecasting, and decision algorithms. This role involves end-to-end ownership of data science projects – from data exploration and feature engineering to model deployment – with the goal of delivering actionable insights and driving business outcomes. Key Responsibilities: • Design, develop, and implement machine learning models (supervised, unsupervised, and reinforcement learning) to solve business problems. • Apply statistical methods including regression, hypothesis testing, and experimental design to analyze and interpret complex datasets. • Build and optimize models for classification, clustering, recommendation systems, forecasting, and anomaly detection. • Develop Natural Language Processing (NLP) solutions, such as sentiment analysis, entity recognition, text classification, summarization, and conversational AI. • Apply decision algorithms and search algorithms to optimize problem-solving in operations, logistics, personalization, and AI-driven solutions. • Conduct time series forecasting using ARIMA, Prophet, LSTM, or other advanced methods for demand prediction and trend analysis. • Perform feature engineering, data cleaning, and exploratory data analysis (EDA) to ensure high-quality model inputs. • Collaborate with cross-functional teams (engineering, product, business) to identify opportunities and deploy AI-driven solutions. • Implement and maintain MLOps pipelines for scalable and reproducible model deployment. • Translate complex models and findings into clear insights, dashboards, and presentations for stakeholders. • Stay updated with cutting-edge developments in AI/ML, NLP, and optimization techniques to continuously improve solutions. Required Skills & Qualifications: • Bachelor’s/Master’s degree in Computer Science, Data Science, Statistics, Applied Mathematics, or a related field. • Proven experience (3–8+ years) in data science and applied machine learning. • Strong expertise in statistical methods (regression, hypothesis testing, probability, time series). • Proficiency in Python (NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, Keras, NLTK, SpaCy, Hugging Face) or R. • Hands-on experience with classification, clustering, forecasting, and recommendation systems. • Solid background in NLP techniques (word embeddings, transformers, LLM fine-tuning, text mining). • Understanding of decision trees, optimization, search algorithms, and reinforcement learning. • Experience with SQL, NoSQL, and big data technologies (Spark, Hadoop, Databricks preferred). • Familiarity with cloud platforms (AWS, Azure, GCP) for ML deployment. • Excellent problem-solving, analytical thinking, and communication skills.