Data Scientist: SMB Analytics & Growth

H&R Block; Missouri; On-site; USD 91,000 - 146,000; Full time

Benefits offered by this job

Medical coverage

401(k) plan

Associate Tax Prep benefit

Discount program

Job summary

H&R Block is hiring a Data Scientist for Small Business Analytics to drive data‑driven insights across the SMB organization. You’ll partner with the DS&A team to translate questions into analytics, develop models, perform exploratory analysis, and deliver actionable findings that inform growth, client engagement, and operational efficiency.

You’ll work across data extraction, feature development, model validation, and communication of results to technical and non‑technical audiences, with

Qualifications

• Bachelors or Masters in Data Science, Statistics, Economics, CS or related field.
• 2–4 years in data science, analytics, or related role.
• Experience applying statistical analysis and ML to business problems.
• Proficiency in Python or R and SQL for data extraction and analysis.

Responsibilities

• Translate business questions into analytical approaches and deliverables.
• Support end‑to‑end analytics projects including data extraction, cleaning and modeling.
• Build and analyze predictive/descriptive models for segmentation, behavior, campaigns, and ops.
• Conduct exploratory data analysis to identify trends and opportunities in SMB data.
• Collaborate with product, marketing and operations to align analytics with goals.
• Communicate results through presentations, dashboards, or summaries.
• Contribute to production analytics with engineering teams and ensure reproducibility.

Skills

Python

R

SQL

Statistics

Machine learning

Education

DS/Statistics/CS degree

Tools

SQL

Job description

H&R Block is hiring a Data Scientist for Small Business Analytics to drive data‑driven insights across the SMB organization. You’ll partner with the DS&A team to translate questions into analytics, develop models, perform exploratory analysis, and deliver actionable findings that inform growth, client engagement, and operational efficiency.

You’ll work across data extraction, feature development, model validation, and communication of results to technical and non‑technical audiences, with