Senior Data Scientist, Applied AI and Agentic Solutions Engineer

Model complex business problems and discovering business insights using statistical, algorithmic, mining, and visualization techniques. The data scientist conducts experiments and methodologies to generate and collect data for business use. Mines available data to identify trends and patterns and generates insights for LOBs and senior leadership Partners with LOBs to identify questions and issues for data analysis and experiments Performs complex statistical analysis on experimental or business data to validate and quantify trends or patterns Constructs predictive models, algorithms, and probability engines to support data analysis or product functions; verifies model and algorithm effectiveness based on real-world results Identifies meaningful insights from large data and metadata sources; interprets and communicates insights and findings from analysis and experiments to product, service, and business managers Develops and codes software programs, algorithms, and automated processes to cleanse, integrate, and evaluate large datasets from multiple disparate sources Researches and applies knowledge of existing and emerging data science principles, theories, and techniques to inform business decisions Uses advanced mathematical and statistical concepts and theories to analyze and collect data and construct solutions to business problems Participates in research and implements cutting-edge techniques and tools in machine learning/deep learning/artificial intelligence to make data analysis more efficient and to create new data-driven capabilities and insights Supports user experience specialists and information architects to enhance information visualization through development of dashboards and user interface best practices to analytics and product teams and provides consultations for their data-based experimentations Assists in communicating Enterprise data governance principles throughout the company Job Specifications Typically has the following skills or abilities: Bachelor’s degree in computer science, data science, statistics, economics, or related functional area; or equivalent experience Six years of demonstrated data analytics and/or data science experience including experience with big data analysis tools and techniques.

Preferably in successfully executing data science projects in one or more of the following domains/business functions: risk modeling, customer behavior prediction, customer journey analytics, marketing analytics, target marketing, churn management, e-commerce platforms, financial risk analytics, logistics/supply chain. With a Master’s degree or higher, six or more years of relevant experience required.

Experience building and deploying predictive models, web scraping, and scalable data pipelines Experience using statistical modeling and machine learning to solve complex business problems. Experience in data discovery/analysis platforms such as SPSS Modeler, KNIME, or similar. Coding knowledge and experience in languages such as R, Python/Jupyter, SAS, Java, Scala, C++, etc. Experience with database programming languages such as SQL, PL/SQL, and others for relational databases, and preferably experience in nonrelational databases such as NoSQL, Hadoop, MongoDB, Cassandra, and others Flexible and able to change priorities and direction quickly and effectively Excellent written and verbal communication, presentation and analytical skills Strategic skills, business acumen and curiosity to support envisioning work, program planning and strategic partnerships Ability to regularly exercise discretion and independent judgment in the performance of his/her job duties Remain current in the field, including new techniques, approaches, and software available For roles that are remote (i.e., Work From Home (WFH)) or hybrid (i.e., partial onsite at a VSP location and WFH), must demonstrate a high level of engagement in virtual environments, including maintaining camera presence during meetings to support effe