Job Details

Data Scientist

Zurich (Schaumburg, IL) seeks a Data Scientist to use a combination of statistical analysis, data science, machine learning, and artificial intelligence techniques to solve our business partners' most pressing problems and help our customers better understand their risks. Specific duties include: develop & validate supervised & unsupervised learning models, create machine learning and AI models, and use other statistical techniques to solve business problems; design and develop data science, machine learning, and AI-based systems to deliver meaningful technology to the business; contribute to the development of a strategy on how to use the model/solution to generate impact; collaborate with business stakeholders to understand their challenges and develop an analytical solution that creates business impact; contribute to the effort for team to democratize data by consolidating, integrating, cleansing, and minimally curating operational production system data and external data for insight generation; perform exploratory analysis which includes understanding the key statistical metrics on data columns, determining the granularity of the data, & assessing any related merge keys for combining the data; develop a production, end to end solution for deployment, working closely with Data Engineers and MLOps teams; contribute to the development of monitoring framework to ensure the tool is performing as intended; support stakeholders after deployment to ensure impact is achieved; contribute to the development and maintenance of best practices. Option to work remotely from anywhere within the state of IL.

Position requires a Master's degree, or foreign equivalent, in Computer Science, Business Analytics, or a closely related field of study, plus 4 years of experience in the job offered, or as a Lead Data Science Analyst, Lead Data Scientist, or similar position using statistical analysis, data science, machine learning, and artificial intelligence techniques to solve business problems and understand risks. Must have 4 years of experience with each of the following: using statistical analysis and data science techniques to solve business problems and understand risks; working with ML algorithms including regression, classification, clustering, and decision trees; working with data science tools and libraries including Python and SQL; working with Cloud platforms including AWS and Google Cloud; doing dashboard reporting using Tableau; communicating with business unit stakeholders and cross-functional teams to deliver data results; and working with underpinnings of theory involving statistical modeling concept. Must also have 2 years of experience with each of the following: doing NLP tasks including document classification, entity extraction, and summarization; using machine learning, and artificial intelligence techniques; and working with data science tools and libraries including Pandas, NumPy, and Scikit-learn. Option to work remotely from anywhere within the state of IL.

Full time position. Apply by submitting your resumes at Zurichna.com/en/careers, Job ID: 127464.

At Zurich, compensation for roles is influenced by a variety of factors, including but not limited to the specific office location, role, skill set, and level of experience. In compliance with local laws, Zurich commits to providing a fair and reasonable compensation range for each role. For more information about our Total Rewards, please click here. Additional rewards may encompass short-term incentive bonuses and merit increases. We encourage candidates with salary expectations beyond the provided range to apply, as they will be considered based on their experience, skills, and education. The salary indicated represents a nationwide market range and has not been adjusted for geographic differentials pertaining to the location where the position may be filled. The proposed salary range for this position is $142,210.

Zurich in North America is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race/ethnicity, color, religion, sex, sexual orientation, gender identity, national origin, disability, or protected veteran status.