CPT Data Science Engineer Jobs
Data Science Engineer jobs on CPT require your work to be directly tied to your enrolled program, so roles that combine statistical modeling, ML pipeline development, and data infrastructure align well. Your DSO must authorize CPT before you start, and part-time CPT (under 20 hours weekly) keeps your full-time CPT eligibility intact for later.
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Get Access To All JobsINTRODUCTION
As a Data Science/Data Engineer Intern, you will work on cutting-edge analytical and data engineering projects that drive measurable business impact across pricing, underwriting, marketing, and claims. This internship is ideal for a technically curious, motivated problem-solver who wants hands-on data science experience.
Responsibilities
- Support the design, construction, and optimization of robust data pipelines to enable machine learning and analytical modeling.
- Contribute to the design and implementation of data and ML workflows using orchestration tools such as Dagster, Airflow, or similar frameworks.
- Help implement data quality checks, validation routines, and monitoring for automated data workflows.
- Assist in organizing and managing internal GitHub repositories to standardize ML project structures and best practices.
- Collaborate with data scientists and engineers to automate the ingestion, transformation, and delivery of data for model development.
- Contribute to initiatives migrating analytical processes into cloud-based data lake architectures and modern platforms such as AWS or Snowflake.
- Develop reusable and well-tested code to support analytical pipelines and internal tools using Python and SQL.
- Conduct data mining, cleansing, and preparation tasks to build high-quality analytical datasets.
- Participate in model development, including data profiling, model training, validation, and interpretation.
- Build and evaluate predictive models that enhance profitability through improved segmentation and estimation of insurance risk.
- Assist in studies evaluating new business models for customer segmentation, retention, and lifetime value.
- Collaborate with business leaders to translate insights into operational improvements and cost efficiencies.
QUALIFICATIONS
- Currently pursuing or recently completed a Master’s in Data Science, Computer Science, Statistics, Economics, or related field.
- Proficiency in Python (Pandas, NumPy, Scikit-learn, XGBoost, or PyTorch) and SQL.
- Understanding of data engineering concepts, ETL/ELT workflows, and machine learning deployment.
- Exposure to workflow orchestration tools (e.g., Airflow, Dagster, Prefect) and Git/GitHub for collaborative development.
- Familiarity with Docker, CI/CD pipelines, and infrastructure-as-code tools such as Terraform preferred.
- Knowledge of AWS cloud services such as S3, Lambda, EC2, or SageMaker a plus.
- Experience with common modeling techniques (e.g., GLM, tree-based models, Bayesian statistics, NLP, deep learning) through coursework or projects.
- Strong analytical, communication, and problem-solving skills.
- A self-starter mindset, with attention to detail and enthusiasm for learning new technologies.
SALARY RANGE
The pay range for this position is $35 hourly.
ABOUT THE COMPANY
The Plymouth Rock Company and its affiliated group of companies write and manage over $2 billion in personal and commercial auto and homeowner’s insurance throughout the Northeast and mid-Atlantic, where we have built an unparalleled reputation for service. We continuously invest in technology, our employees thrive in our empowering environment, and our customers are among the most loyal in the industry. The Plymouth Rock group of companies employs more than 1,900 people and is headquartered in Boston, Massachusetts. Plymouth Rock Assurance Corporation holds an A.M. Best rating of “A-/Excellent."
INTRODUCTION
As a Data Science/Data Engineer Intern, you will work on cutting-edge analytical and data engineering projects that drive measurable business impact across pricing, underwriting, marketing, and claims. This internship is ideal for a technically curious, motivated problem-solver who wants hands-on data science experience.
Responsibilities
- Support the design, construction, and optimization of robust data pipelines to enable machine learning and analytical modeling.
- Contribute to the design and implementation of data and ML workflows using orchestration tools such as Dagster, Airflow, or similar frameworks.
- Help implement data quality checks, validation routines, and monitoring for automated data workflows.
- Assist in organizing and managing internal GitHub repositories to standardize ML project structures and best practices.
- Collaborate with data scientists and engineers to automate the ingestion, transformation, and delivery of data for model development.
- Contribute to initiatives migrating analytical processes into cloud-based data lake architectures and modern platforms such as AWS or Snowflake.
- Develop reusable and well-tested code to support analytical pipelines and internal tools using Python and SQL.
- Conduct data mining, cleansing, and preparation tasks to build high-quality analytical datasets.
- Participate in model development, including data profiling, model training, validation, and interpretation.
- Build and evaluate predictive models that enhance profitability through improved segmentation and estimation of insurance risk.
- Assist in studies evaluating new business models for customer segmentation, retention, and lifetime value.
- Collaborate with business leaders to translate insights into operational improvements and cost efficiencies.
QUALIFICATIONS
- Currently pursuing or recently completed a Master’s in Data Science, Computer Science, Statistics, Economics, or related field.
- Proficiency in Python (Pandas, NumPy, Scikit-learn, XGBoost, or PyTorch) and SQL.
- Understanding of data engineering concepts, ETL/ELT workflows, and machine learning deployment.
- Exposure to workflow orchestration tools (e.g., Airflow, Dagster, Prefect) and Git/GitHub for collaborative development.
- Familiarity with Docker, CI/CD pipelines, and infrastructure-as-code tools such as Terraform preferred.
- Knowledge of AWS cloud services such as S3, Lambda, EC2, or SageMaker a plus.
- Experience with common modeling techniques (e.g., GLM, tree-based models, Bayesian statistics, NLP, deep learning) through coursework or projects.
- Strong analytical, communication, and problem-solving skills.
- A self-starter mindset, with attention to detail and enthusiasm for learning new technologies.
SALARY RANGE
The pay range for this position is $35 hourly.
ABOUT THE COMPANY
The Plymouth Rock Company and its affiliated group of companies write and manage over $2 billion in personal and commercial auto and homeowner’s insurance throughout the Northeast and mid-Atlantic, where we have built an unparalleled reputation for service. We continuously invest in technology, our employees thrive in our empowering environment, and our customers are among the most loyal in the industry. The Plymouth Rock group of companies employs more than 1,900 people and is headquartered in Boston, Massachusetts. Plymouth Rock Assurance Corporation holds an A.M. Best rating of “A-/Excellent."
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Get Access To All JobsData Science Engineer CPT: Frequently Asked Questions
Does a Data Science Engineer role qualify for CPT authorization?
Yes, if the work is an integral part of your degree program and your DSO approves it. Roles involving ML model development, data pipeline engineering, or statistical analysis map directly to computer science, data science, and engineering curricula. Your DSO will want to see how specific job duties connect to your enrolled courses before issuing the authorization.
Can I do CPT part-time as a Data Science Engineer while finishing classes?
Yes, and part-time CPT is often the right structure during the academic year. Working under 20 hours weekly preserves your full-time CPT eligibility, which matters if you want to use it for a full-time role before graduation. Your DSO authorizes each CPT period separately, so you'll need a new I-20 endorsement each semester or session you work.
How do I find Data Science Engineer employers who understand CPT work authorization?
Migrate Mate filters employer listings by LCA filing history, which identifies companies already experienced with work authorization processes. Data science and engineering roles at tech, finance, and healthcare companies tend to have the most active LCA filings, meaning their HR and legal teams are less likely to stall when you explain CPT at the offer stage.
What should my CPT offer letter include for a Data Science Engineer position?
It must include your job title, start and end dates, work location, weekly hours, and a description of duties tied to your field of study. For data science roles, duties like model training, feature engineering, or data infrastructure development are specific enough to satisfy most DSOs. Vague language like 'assist with projects' is often rejected and requires a revised letter.
Does CPT experience as a Data Science Engineer strengthen a future H-1B petition?
CPT work counts as qualifying experience for H-1B visa specialty occupation petitions if the role required a bachelor's degree or higher in a directly related field. USCIS evaluates the substantive nature of the work, not just the title, so documenting your responsibilities, tools used, and outcomes during CPT creates a stronger evidence record for future petitions.