Specialist II - Data Science

Role Overview: As a Data Scientist at UST, you will independently develop data-driven solutions to tackle complex business challenges by utilizing analytical, statistical, and programming skills to collect, analyze, and interpret large datasets under supervision. Your role involves working closely with stakeholders across the organization to identify opportunities for leveraging customer data in creating models that generate valuable business insights. You will be responsible for creating new experimental frameworks, building automated tools for data collection, correlating similar datasets, and deriving actionable results. Additionally, you will develop predictive models and machine learning algorithms to analyze vast amounts of information, uncover trends, and patterns. By mining and analyzing data from company databases, you will drive optimization and improvement in product development, marketing techniques, and business strategies. Moreover, you will be expected to create processes and tools to monitor and analyze model performance, data accuracy, and develop data visualization and illustrations to address business problems effectively. Key Responsibilities: - Apply statistical techniques like regression, properties of distributions, and statistical tests to analyze data - Utilize machine learning techniques such as clustering, decision tree learning, and artificial neural networks for data analysis - Create advanced algorithms and statistics through regression, simulation, scenario analysis, and modeling - Visualize and present data for stakeholders using tools like Periscope, Business Objects, D3, ggplot, etc. - Oversee the activities of analyst personnel, ensuring efficient execution of their duties - Create efficient and reusable code for data improvement, manipulation, and analysis - Manage project codebase through version control tools like git and bitbucket - Create reports depicting trends and behaviors from analyzed data - Train end users on new reports and dashboards - Document work, conduct peer reviews, manage knowledge, and report task status Qualifications Required: - Excellent pattern recognition and predictive modeling skills - Strong background in data mining and statistical analysis - Expertise in machine learning techniques and advanced algorithm creation - Analytical, communication, critical thinking, attention to detail, mathematical, and interpersonal skills - Proficiency in programming languages such as Java, Python, R, web services like Redshift and S3, statistical and data mining techniques, computing tools, analytical languages, data visualization software, mathematics, spreadsheet tools, DBMS, operating systems, and project management tools - Strong understanding of statistical concepts, SQL, machine learning (Regression and Classification), deep learning (ANN, RNN, CNN), advanced NLP, computer vision, Gen AI/LLM, AWS Sagemaker/Azure ML/Google Vertex AI, and basic implementation experience of Docker, Kubernetes, kubeflow, MLOps, Python (numpy, panda, sklearn, streamlit, matplotlib, seaborn),