Company Overview

The Enlyte Family of Businesses

Mitchell | Genex | Coventry

Enlyte is the parent brand of Mitchell, Genex and Coventry, an organization unlike any other in the Property & Casualty industry, bringing together three great businesses with a shared vision of using technology innovation, clinical services and network solutions to help our customers and the people they serve. Our suite of products and services enable our employees to help people recover from challenging life events, while providing opportunities for meaningful impact and career growth.

Job Description

We are building next generation suite of smart product solutions using Computer Vision, Advanced Analytics and Artificial Intelligence [Deep Learning]. We are looking for engineers and technologists to help build the next generation of systems, tools and features for our cutting-edge products and platforms that support millions of transactions. This team is the focal point in our work, bringing the latest in search and discovery ideas to production on a large scale.

As a remote Machine Learning Data Scientist Intern, you will have the opportunity to solve challenging problems or build predictive models across a broad range of products. You will apply machine learning techniques to improve our algorithms, workflows and core products to become more predictive. You will partner with engineers to implement your ideas in production and analysts to evaluate and validate your improvements. Interns will be working on real projects and products that are customer-facing.

You will have opportunity to work on several challenging Machine Learning problems, including

• How to build models at scale using vast amounts of structured and unstructured heterogeneous types of data.
• Ensuring high accuracy based on industry’s stringent requirements around precision or recall and with minimum Type I and Type II errors.
• Generating predictions for millions of rows of data with high response time
• Dealing with high data diversity (vast amounts of data will need to be classified and will have multi labelled outcomes)
  Dealing with very high dimensionality (expect to work on large matrix computations, variable transformation & feature engineering and selection using PCA and other novel ML techniques)
• Dealing with noisy data (build models robust enough for unclassified and/or mislabeled data)

Qualifications

Minimum Qualifications:

• Pursuing a bachelor's or master's degree in Mathematics, Computer Science, Data Science, or related degree
• GPA of 3.0 or higher
• Graduating between Summer 2025 and Summer 2026
• Good understanding of machine learning theory, Artificial Intelligence [Deep Learning] and algorithms, such as CNNs, k-NN, Naive Bayes, SVM, Decision Forests, Ensembles, Decisions Trees
• Coding skills and knowledge around using scientific, distributed programming and scripting languages like R, Python, Pyspark and/or Java preferred
• Foundation in statistics and machine learning algorithms
• Familiarity of modern statistical learning methods & machine learning Frameworks like H2O, Spark & Hadoop
• Knowledge on how to build prototypes and be able to understand the existing code base
• A principled approach to solving algorithmic problems with a focus on what will make users happy
• A pragmatic approach to rapidly evaluating new algorithmic ideas
• A very high attention to detail and ability to thoroughly think through problems
• Excellent written and oral communication skills on both technical and non-technical topics
• Ability to commit 40 hours per week for 12 weeks during the 2025 summer
• Working PST or CST time zones preferred, but not required

Learn more about our Summer Internship Program:

https://careers.enlyte.com/internship

Benefits

We’re committed to supporting your ultimate well-being through our total compensation package offerings that support your health, wealth and self. These offerings include Medical, Dental, Vision, Health Savings Accounts / Flexible Spending Accounts, Life and AD&D Insurance, 401(k), Tuition Reimbursement, and an array of resources that encourage a lifetime of healthier living. Benefits eligibility may differ depending on full-time or part-time status. Compensation depends on the applicable US geographic market. The expected base pay for this position is $34.00 hourly, and will be based on a number of additional factors including skills, experience, and education.

The Company is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, gender, gender identity, sexual orientation, age, status as a protected veteran, among other things, or status as a qualified individual with disability.

Don’t meet every single requirement? Studies have shown that women and underrepresented minorities are less likely to apply to jobs unless they meet every single qualification. We are dedicated to building a diverse, inclusive, and authentic workplace, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyway. You may be just the right candidate for this or other roles.

#LI-Remote

#LI-CF1

Minimum Qualifications:

• Pursuing a bachelor's or master's degree in Mathematics, Computer Science, Data Science, or related degree
• GPA of 3.0 or higher
• Graduating between Summer 2025 and Summer 2026
• Good understanding of machine learning theory, Artificial Intelligence [Deep Learning] and algorithms, such as CNNs, k-NN, Naive Bayes, SVM, Decision Forests, Ensembles, Decisions Trees
• Coding skills and knowledge around using scientific, distributed programming and scripting languages like R, Python, Pyspark and/or Java preferred
• Foundation in statistics and machine learning algorithms
• Familiarity of modern statistical learning methods & machine learning Frameworks like H2O, Spark & Hadoop
• Knowledge on how to build prototypes and be able to understand the existing code base
• A principled approach to solving algorithmic problems with a focus on what will make users happy
• A pragmatic approach to rapidly evaluating new algorithmic ideas
• A very high attention to detail and ability to thoroughly think through problems
• Excellent written and oral communication skills on both technical and non-technical topics
• Ability to commit 40 hours per week for 12 weeks during the 2025 summer
• Working PST or CST time zones preferred, but not required

Learn more about our Summer Internship Program:

https://careers.enlyte.com/internship

We are building next generation suite of smart product solutions using Computer Vision, Advanced Analytics and Artificial Intelligence [Deep Learning]. We are looking for engineers and technologists to help build the next generation of systems, tools and features for our cutting-edge products and platforms that support millions of transactions. This team is the focal point in our work, bringing the latest in search and discovery ideas to production on a large scale.

As a remote Machine Learning Data Scientist Intern, you will have the opportunity to solve challenging problems or build predictive models across a broad range of products. You will apply machine learning techniques to improve our algorithms, workflows and core products to become more predictive. You will partner with engineers to implement your ideas in production and analysts to evaluate and validate your improvements. Interns will be working on real projects and products that are customer-facing.

You will have opportunity to work on several challenging Machine Learning problems, including

• How to build models at scale using vast amounts of structured and unstructured heterogeneous types of data.
• Ensuring high accuracy based on industry’s stringent requirements around precision or recall and with minimum Type I and Type II errors.
• Generating predictions for millions of rows of data with high response time
• Dealing with high data diversity (vast amounts of data will need to be classified and will have multi labelled outcomes)
  Dealing with very high dimensionality (expect to work on large matrix computations, variable transformation & feature engineering and selection using PCA and other novel ML techniques)
• Dealing with noisy data (build models robust enough for unclassified and/or mislabeled data)