Developing analytical solutions by applying data science and modeling techniques to deliver useful insights for better decisions and improved business performance.
Requirements
- Ability to show skills in several of following areas: classification, regression, forecasting, clustering, anomaly detection, co-occurrence grouping, similarity matching, profiling, link prediction, dimensionality reduction, tensor decomposition and regression, and causal inference
- Proficiency with at least one programming language such as Python, R, Scala or Java
- Experience with SQL and familiarity with relational databases
- Experience with data visualization tools such as Tableau, PowerBI, or similar
- Experience working with large data sets, distributed computing tools (Map/Reduce, Hadoop, Hive, Spark, etc.) and Machine Learning pipelines (Scikit-learn, DASK, etc.) is preferred
- A strong passion for empirical research and for answering hard questions with data
Responsibilities
- Developing analytical solutions by applying data science and modeling techniques to deliver useful insights for better decisions and improved business performance.
- Performing hands-on analysis, design, and development of analytical solutions
- Performing exploratory and targeted data analyses, which could include complex event and real-time event processing
- Building predictive models and machine learning algorithms
- Analyzing large amounts of diverse information to discover trends and patterns
- Driving the collection of new data and the refinement of existing data sources
- Preparing and cleaning structured and/or unstructured data
Other
- Hybrid: This role is categorized as hybrid. This means the successful candidate is expected to report to IT Innovation Center in Austin, Texas three times per week.
- Must be graduating between December 2026 to August 2028
- Able to work fulltime, 40 hours per week
- Excellent teammate and communicator with strong interpersonal skills
- Cultivates open, inclusive culture that supports learning and encourages collaboration
