Data Scientist

About Get Covered LLC
We provide cost-effective coverage with just a few clicks — satisfying residents, property managers, agencies, and distribution partners with a process that is as simple and touchless as possible.
About The Role

• We are looking for a Data Scientist to support analytics and modeling efforts across the business. This role is ideal for someone early in their data science career who is eager to learn, build strong fundamentals, and apply data to real-world business problems in a fast-growing insurtech environment.
  

You will work closely with engineers, department managers, to analyze data, build models, and help translate insights into actionable recommendations.
What You'll Do

• Assist in building, testing, and maintaining statistical and machine learning models under guidance from senior team members
• Analyze structured datasets to identify trends, anomalies, and opportunities across customer and insurance data
• Write clean, well-documented SQL queries and Python (or R) code for analysis and reporting
• Support A/B tests, experiments, and performance analyses
• Create dashboards, reports, and visualizations to communicate findings to stakeholders
• Help ensure data accuracy and consistency by performing data validation and quality checks
• Document assumptions, methodologies, and results for transparency and knowledge sharing
• Collaborate with cross-functional teams to understand business needs and translate them into data questions
  

Qualifications

• Bachelor’s degree in Data Science, Statistics, Mathematics, Computer Science
• 0–2 years of professional experience in data science, analytics, or a related role
• Working knowledge of Python or R for data analysis
• Excellent SQL skills
• Understanding of fundamental statistics and introductory machine learning concepts
• Strong curiosity, problem-solving skills, and willingness to learn
• Ability to clearly communicate insights with guidance and feedback
  

Preferred Qualifications

• Experience in insurance, fintech, SaaS
• Familiarity with common data science libraries
• Exposure to data visualization tools such as Tableau, Looker, or Power BI
• Experience working with cloud data platforms or modern data stacks
  

Projects involving experimentation or predictive modeling