Remote Associate Data Scientist – ML & Analytics

Visa Hunt; United States; On-site; USD 84,000 - 162,000; Full time

Benefits offered by this job

Paid time off

401(k) with company match

Medical, dental, vision

Educational assistance

Job summary

Mercury Insurance in the United States is seeking a data science intern to work on analytical projects that identify business opportunities and develop data-driven solutions. The role requires applying data, statistical models and machine learning techniques while collaborating with software engineers, data analysts and product leaders.

The internship offers exposure to cross-functional teams, hands-on project work, and opportunities to present findings with dashboards and PowerPoint.

Qualifications

• Bachelor’s degree in math, statistics, computer science or related area; Master’s preferred.
• 2+ years of data mining and data/statistical analysis experience; internship experience a plus.
• Experience with SQL and statistical software (Python, R, SAS) required.

Responsibilities

• Identify business opportunities and answer business questions using data and ML techniques.
• Collaborate with engineers, analysts and product leaders on cross-functional projects.
• Develop and implement plans; create reports, dashboards and presentations.
• Collect, clean and prepare data; monitor data quality and analysis processes.
• Communicate findings to SMEs and management with clear visuals.

Skills

Data mining

Machine learning

Python

R

SQL

Statistical analysis

Communication

Education

Bachelor’s degree in math/statistics/CS

Master’s Degree preferred

Tools

Python

R

SAS

SQL

Job description

Mercury Insurance in the United States is seeking a data science intern to work on analytical projects that identify business opportunities and develop data-driven solutions. The role requires applying data, statistical models and machine learning techniques while collaborating with software engineers, data analysts and product leaders.

The internship offers exposure to cross-functional teams, hands-on project work, and opportunities to present findings with dashboards and PowerPoint.