Data Science Intern

SageSure

Jersey City, NJ, United States5d ago

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Key details

Location
Jersey City, NJ, United States
Work style
Onsite
Level
Intern
Job type
Internship
Function
Data & ML
Focus area
AI / ML
Posted
5d ago

Skills

cloud computingdata analysisdata visualizationdatabricksmachine learningpythonrrelational databasessqlstatistical modeling

About the role

Overview: 

If you're looking for the stability of a profitable, growing company with the entrepreneurial spirit of a startup, we’re hiring. SageSure, a leader in catastrophe-exposed property insurance, is seeking an Intern to join the Rising Pioneer Program as part of our Data Science team. 

Over the course of this 10-week program, interns will gain tangible, hands-on experience and insight into our business operations. After 3 days of orientation and training, you’ll join our Data Science team, where you’ll be assigned projects with unlimited opportunity for challenges and achievement. We have, very often, considered our interns for post-graduation roles within the company. 

What you’d be doing: 

  • Learn and network with employees, leaders, and other interns during an on-the-job experience. 
  • Potential to earn college credit. 
  • Provide research and analysis support on ad-hoc projects. 
  • Fulfill tasks and project assignments set out by team leaders. 
  • Receive coaching, mentoring, and feedback from knowledgeable SageSure professionals. 
  • Support the development, testing, and evaluation of data science models and analytical solutions. 
  • Assist with collecting, cleaning, transforming, and analyzing structured and unstructured data. 
  • Explore datasets to identify trends, patterns, relationships, and opportunities that can inform business decisions. 
  • Apply statistical and analytical techniques to support business questions and data-driven problem solving. 
  • Partner with Data Scientists, Data Engineers, and business stakeholders to understand project objectives and translate business needs into analytical approaches. 
  • Assist with model validation, performance evaluation, and documentation of analytical methods and results. 
  • Develop visualizations, summaries, and presentations that clearly communicate findings to both technical and non-technical audiences. 
  • Support experimentation and testing to evaluate model performance, business impact, or potential improvements. 
  • Participate in team meetings, project discussions, and technical reviews. 
  • Learn and apply data science best practices related to reproducibility, documentation, testing, and responsible use of data. 

We’re looking for someone who has: 

  • Is currently enrolled in a relevant degree program with a focus on Data Science, Statistics, Mathematics, Computer Science, Economics, Engineering, or a related quantitative field, with an anticipated graduation date in 2028. 
  • Has foundational experience working with data through coursework, academic projects, research, or prior work experience. 
  • Has experience with Python, R, SQL, or another programming or analytical language. 
  • Demonstrates strong analytical, quantitative, problem-solving, and critical-thinking skills. 
  • Has a basic understanding of statistics, data analysis, or machine learning concepts. 
  • Is comfortable working with data and interpreting analytical results. 
  • Has strong written and verbal communication skills and can explain technical concepts in a clear and understandable way. 
  • Is detail-oriented, curious, and willing to explore different approaches to solving problems. 
  • Is comfortable multitasking and eager to learn new tools, technologies, and analytical techniques. 
  • Has the ability to work independently as well as collaboratively as a team member. 
  • Is authorized to work in the United States. 

Highly preferred candidates also have: 

  • Prior internship, research, technical project, or relevant professional experience. 
  • GPA of 3.0 or higher. 
  • Experience using Python for data analysis, modeling, or machine learning. 
  • Familiarity with SQL and relational databases. 
  • Exposure to machine learning techniques, statistical modeling, or predictive analytics. 
  • Experience with data visualization tools or libraries. 
  • Familiarity with cloud platforms, Databricks, or other modern data and analytics technologies. 
  • Experience presenting analytical findings or recommendations to non-technical audiences. 

Data and AI at SageSure:  

At SageSure, data and AI

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