The Data Scientist will support UL Standards & Engagement (ULSE) by analyzing complex data to identify trends and opportunities that inform standards development and contribute to the advancement of evidence-based decision-making. The role aims to enable the organization to anticipate emerging issues, measure effectiveness, and support the continuous improvement of safety standards.
Requirements
- Demonstrated proficiency in data science concepts, tools, methodologies.
- Full understanding of the data science project lifecycle and ability to develop analytical solutions.
- Strong technical aptitude in statistical and machine learning methods and predictive analytics with ability to evaluate complex datasets and translate insights into actionable recommendations.
- Experience manipulating large datasets, utilizing databases for advanced data management, and familiarity with general purpose programming language such as Hadoop.
- Proficiency in Python, SQL, or similar programing languages for data analysis and modeling.
- Experience in Natural Language Processing (NLP) preferred.
- Experience developing project timelines, scope, and managing project resources.
Responsibilities
- Independently lead data science projects from design through implementation.
- Develop and validate models, interpret complex datasets, and translate insights into actionable recommendations.
- Formulate analytical approaches to solve a range of complex problems.
- Perform data analysis, statistical modeling, and predictive analytics to identify trends, opportunities, and insights that support organizational goals.
- Aggregate, transform, and integrate large, diverse datasets from retrospective and real-time sources to build robust analytical models, test hypotheses, and identify emerging trends.
- Design and implement software systems, analytical pipelines, and algorithms to automate data processing, conduct scalable analyses, and enable real-time data insights.
- Leverage Azure OpenAI for developing advanced generative AI applications, including implementing function-calling features for streamlined model integration.
Other
- Bachelor’s degree in Data Science, Computer Science, Statistics, Engineering or related field. Advanced degree preferred.
- Minimum 3 years of related work experience in data and statistical analysis.
- Effective communication and engagement skills, with ability to convey complex information to various stakeholder group, including technical and non-technical audiences.
- Positive and collaborative interpersonal skills, able to foster partnership and drive internal knowledge sharing across teams or functions.
- Adaptability in navigating ambiguity and weighing trade-offs across modeling techniques, tools, and solution strategies.
