H&R Block is seeking to leverage advanced statistical modeling, machine learning, and data engineering techniques to drive strategic insights and develop scalable predictive solutions across its products and services.
Requirements
- Proven expertise in applying advanced analytical techniques, including ensemble algorithms (e.g., bagging, boosting, GBM, random forest)
- Winner-take-all methods (e.g., SVM, KNN)
- Regression techniques (e.g., Ridge, Lasso, Polynomial, SHAP)
- Strong proficiency in Python or R, with a focus on applied theory and model interpretability
- Experience with big data and machine learning frameworks such as PySpark and SQL
- Skilled in data visualization using libraries like Matplotlib, Seaborn, ggplot2, and Plotly
- Deep understanding of data architectures, APIs, and data warehousing solutions
Responsibilities
- Design, develop, and deploy advanced statistical and machine learning models to support business decisions and optimize client experiences
- Utilize ensemble methods (e.g., bagging, boosting, gradient boosting machines, random forest) and winner-take-all algorithms (e.g., SVM, KNN) for predictive analytics and classification tasks
- Apply regression techniques including Ridge, Lasso, and polynomial regression, and leverage interpretability tools such as SHAP values
- Work with large-scale data sets and frameworks including Hadoop, Spark, PyTorch, TensorFlow, or similar technologies
- Collaborate with engineering teams to integrate analytical models into production systems through APIs and data pipelines
- Create clear, compelling data visualizations using Python or R libraries such as Matplotlib, Seaborn, ggplot2, and Plotly
- Maintain a strong understanding of data architecture, warehousing, and governance using tools such as Pig, MapReduce, Spark, and Hive
Other
- Masters degree in a related field or the equivalent through a combination of education and related work experience
- Minimum of 5 years of professional experience in data science or a related field
- Demonstrated ability to work independently in fast-paced environments, managing multiple priorities and collaborating with diverse business stakeholders
- Strong communication skills with the ability to present findings to technical and non-technical audiences
- Ability to translate complex data insights into actionable business strategies
