Data Science Engineer

We are seeking a talented Data Science Engineer to join our team and contribute to the development and implementation of advanced data solutions using technologies such as AWS Glue, Python, Spark, Snowflake Data Lake, S3, SageMaker, and machine learning (M/L).

As a Data Science Engineer, you will play a crucial role in designing, building, and optimizing data pipelines, machine learning models, and analytics solutions. You will work closely with cross-functional teams to extract actionable insights from data and drive business outcomes.

Essential Functions and Responsibilities:

• and maintain ETL pipelines using AWS Glue for data ingestion, transformation, and integration from various sources.
• Python and Spark for data preprocessing, feature engineering, and model development.
• and implement data lake architecture using Snowflake Data Lake, Snowflake data warehouse and S3 for scalable and efficient storage and processing of structured and unstructured data.
• SageMaker for model training, evaluation, deployment, and monitoring in production environments.
• with data scientists, analysts, and business stakeholders to understand requirements, develop predictive models, and generate actionable insights.
• exploratory data analysis (EDA) and data visualization to communicate findings and trends effectively.
• updated with advancements in machine learning algorithms, techniques, and best practices to enhance model performance and accuracy.
• data quality, integrity, and security throughout the data lifecycle by implementing robust data governance and compliance measures.

Qualifications and Education:

• degree or higher in Computer Science, Data Science, Statistics, or related field.
• in AWS services such as Glue, S3, SageMaker, and Snowflake Data Lake with 5-6 years of experience.
• programming skills in Python for data manipulation, analysis, and modeling.
• with distributed computing frameworks like Spark for big data processing.
• of machine learning concepts, algorithms, and tools for regression, classification, clustering, and recommendation systems.
• with data visualization tools with Tableau for creating meaningful visualizations.
• problem-solving, analytical thinking, and communication skills.
• to work collaboratively in a team environment and manage multiple priorities effectively.
• deploying machine-learning models in production environments and monitoring their performance.
• of MLOps practices, model versioning, and automated model deployment pipelines.
• with SQL, NoSQL databases, and data warehousing concepts.
• understanding of cloud computing principles and architectures.
• in AWS, Python, Spark, or related technologies.

About the Company:

The Plymouth Rock Company and its affiliated group of companies write and manage over $1.8 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 2,000 people and is headquartered in Boston, Massachusetts. Plymouth Rock Assurance Corporation holds an A.M. Best rating of “A-/Excellent”.

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