Data Scientist (ML Infrastructure)

Job Title: Data Scientist (Client Infrastructure) Location: San Antonio, TX Type: Contract Competencies: Digital : Data Science, Digital : Python for Data Science Role Description: Client Infrastructure Development: Design and develop the Client infrastructure, including data ingestion, storage, and management systems. Implement and maintain version control systems for Client models and datasets. Develop and deploy automated Client workflows using tools such as TensorFlow, PyTorch, or Scikit-learn. Model Deployment: Collaborate with data scientists to develop and deploy Client models into production environments. Ensure the smooth operation of deployed models by monitoring performance and identifying potential issues. Implement model serving infrastructure using tools such as TensorFlow Serving or Hugging Face Transformers. Data Management: Develop and maintain data ingestion, storage, and management systems for Client workflows. Ensure the quality and integrity of data used in Client models by implementing data validation and cleaning processes. Implement data security measures to protect sensitive data. Monitoring and Optimization: Develop and maintain monitoring and logging systems for Client workflows. Identify potential issues with deployed Client models and work with data scientists to resolve them. Implement optimization techniques to improve the performance of Client models in production. Collaboration and Communication: Work closely with cross-functional teams, including data scientists, software engineers, and DevOps engineers. Develop and maintain documentation for Client infrastructure and workflows. Present findings and recommendations to stakeholders through clear and effective communication. Desirable Skills: Programming: Python, R Programing, Power BI, MySQL Server, Tableau, MS Excel Tools : NumPy, Pandas, Sklearn, Seaborn, Matplotlib, PyTorch, Statsmodels, NLTK Techniques : Time Series Analysis, Linear Regression, Random Forest, Decision Tree, Descriptive Statistics,Exploratory Data Analysis (EDA), Data Preprocessing, Statistical Analysis, Machine Learning, Deep Learning Soft Skills : Problem Solver, Self-learner, Communication, Adaptability, Creativity, Time Management, Presentation Skills, Conflict Resolution, Stress Management