The Senior Data Scientist position will analyze large sets of data using statistical software to identify trends, patterns, and correlations that inform forecasting models. Develop mathematical models and apply feature selection algorithms to models predicting business outcomes. Write new natural language processing (NLP) functions in programming languages to conduct analyses on text data. Identify solutions to business problems and drive business decisions using the results of data analysis, using techniques like sentiment analysis, topic modeling, and named entity recognition. Propose solutions to business problems using mathematical theories and techniques such as classification, regression, clustering, and recommendation systems. Utilize scikit-learn, TensorFlow, and PyTorch to build and train models. Write efficient and well-documented code in Python, R, and SQL to extract, transform, and load data. Develop data pipelines and architectures to support data-driven decision-making. Design and implement cloud-based data architectures using Azure or Amazon Web Services (AWS) or Google Cloud Platform. Utilize cloud-based services like Databricks or Azure ML or Sagemaker, and Cloud Storage to build and deploy machine learning models. Collect, analyze, and interpret large datasets to identify trends, patterns, and insights. Create graphs, charts, and other visualizations to convey the results of data analysis to stakeholders using Tableau or PowerBI. Deliver oral and written presentations of the results of mathematical modeling and data analysis to non-technical stakeholders, including business leaders and product managers. Collaborate with cross-functional teams, including engineering, product, and marketing, to drive business outcomes.