Data Scientist

Data Scientist Position The following are the duties of this position at the full working level. If this vacancy includes more than one grade and you are selected at a lower grade level, you will have the opportunity to learn to perform these duties and receive training to help you grow in this position. Serves as a Data Scientist on advanced analytics projects by interpreting requirements, contributing to solution designs, and delivering data science tasks and artifacts. Responsibilities include code and model reviews, coordination for acceptance of deliverables, and clear communication within and outside the team. The incumbent may provide training, mentor junior team members, and drive improvements to the analytics environment while aligning solutions to business needs. Key technical duties include developing predictive and clustering models, performing feature engineering, and cleaning datasets to optimize them for analysis. The incumbent collaborates on machine learning (ML) deployment pipelines to ensure models are efficiently operationalized and integrated into production environments. Additionally, they apply techniques to validate the performance of data science models and artificial intelligence (AI), ensuring responsible AI implementation aligned with governance principles. The incumbent contributes to streamlined designs for data extraction, transformation, governance, and cataloguing, enabling insights from prepared data. They apply expertise in computer science, mathematics, and statistical techniques to design complex analytical models, interpret results, and report quantitative trends or relationships effectively and efficiently. Works with the senior data scientist to define advanced analytics, Machine Learning (ML), and AI project objectives, including metrics and measures of effectiveness and expected outcomes. Collaborates to identify and develop innovative methodologies for quantitative analysis, forecasting, predictive modeling, optimization, natural language processing, and large language models, while validating analysis and outcomes. The incumbent is responsible for coding and developing algorithms using advanced tools and platforms such as Python, R, Tableau, SQL, Databricks, Graph Databases, and other modern analytics environments. These tools support data manipulation, processing, visualization, and the articulation of findings through reports and dashboards, to enhance real-time insights and decision-making.