Data Internship, AI/ML and Data Engineering
CoalitionAbout the role
Our Data team will be hiring three interns this summer, focusing on AI/ML and Data Engineering. These particular internship opportunities will be contributing to the vital efforts of our data team, helping define, model, and solve real-world, ambitious, insurance problems using various data-driven approaches.
Curious about the day in the life of an intern?
- Interns at Coalition will be able to work remotely thus giving you the flexibility of working in an environment of your choice
- Did I mention that our internships are paid and full-time?
- You will be paired with your very own mentor that will be your source of guidance and direction during your internship
- Duration: 10-14 weeks (ideally)
- An intern project will be decided between you and your mentor
- The ability to meet senior technical and business leaders across the company
- At the end of your internship, you will have the ability to showcase your completed project and reflect on your time at Coalition
- You will gain some exceptional experience in a fast-paced, fun and inclusive environment
- PLUS...there could be potential for post-internship career opportunities
We believe in saying "yes" when it comes to venturing into the ever-changing world of tech. Your fellow teammates are right there with you. All of our individual successes contribute to the larger success of the company. One for all and all for one!
It’s that time. Let’s take a closer look at the role responsibilities and qualifications.
Responsibilities
AI / Machine Learning
- Identify predictors and causes of business related problems, implement novel approaches related to forecasting/prediction, and present written business recommendations.
- Design and implement tools and frameworks to be used across various machine learning and data science teams
- A strong desire to help build components of our Machine Learning platform that will be used by internal and external Coalition customers.
- Solicit and incorporate feedback on your work from your mentor, other user researchers, and multi-functional team members
Data Engineering
- Identify predictors and causes of business related problems, implement novel approaches related to forecasting/prediction, and present written business recommendations.
- Ability to use data to identify gaps/problems in our customer’s journey and propose potential solutions
- Lead the design and delivery of data models, reporting systems, data automation systems, dashboards and performance metrics that support key product decisions
- Ability to analyze disparate data sources and synthesize into a narrative of what is happening in the data
Skills and Qualifications
- Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Computer Engineering, Statistics, Mathematics or related technical discipline
- You are entering your 4th year at university or final year for an advanced degree
- Strong familiarity with Python, and ability to code and iterate independently on top of data infrastructure tools like Jupyter notebooks, standard ML libraries, Spark, etc.
- Understanding of statistical modeling/machine learning/ data mining concepts, and a track record solving problems with these methods.
- Ability to apply statistical/machine learning techniques such as hypothesis testing, time series forecasting, linear and logistic regression, random forests, etc.
- Ability to participate in a full-time internship between June-August
Compensation
Our compensation reflects the cost of labor across several US geographic markets. The US base salary for this position is $45/hour for the internship. Consistent with applicable laws, an employee's pay within this range is based on a number of factors, which include but are not limited to relevant education, skills, job-related knowledge, qualifications, work experience, credentials, and/or geographic location. Your recruiter can share more on target salary for your location during the interview process. Coalition, Inc. reserves the right to modify this range as needed.