Data Science Engineer
Plymouth Rock Assurance Corporation
Full Time Boston, Massachusetts, United States Posted 5 months ago
About Position
Data Science Engineer (Full Time)
$0.00 / Hourly
Boston, Massachusetts, United States
Data Science Engineer
Full Time Boston, Massachusetts, United States Posted 5 months ago
Description
-Develop and maintain ETL pipelines using AWS Glue for data ingestion, transformation, and integration from various sources.
-Utilize Python and Spark for data preprocessing, feature engineering, and model development.
-Design 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.
-Leverage SageMaker for model training, evaluation, deployment, and monitoring in production environments.
-Collaborate with data scientists, analysts, and business stakeholders to understand requirements, develop predictive models, and generate actionable insights.
-Conduct exploratory data analysis (EDA) and data visualization to communicate findings and trends effectively.
-Stay updated with advancements in machine learning algorithms, techniques, and best practices to enhance model performance and accuracy.
-Ensure data quality, integrity, and security throughout the data lifecycle by implementing robust data governance and compliance measures.
Responsibilities
- -Bachelor's degree or higher in Computer Science, Data Science, Statistics, or related field.
- -Proficiency in AWS services such as Glue, S3, SageMaker, and Snowflake Data Lake with 5-6 years of experience.
- -Strong programming skills in Python for data manipulation, analysis, and modeling.
- -Experience with distributed computing frameworks like Spark for big data processing.
- -Knowledge of machine learning concepts, algorithms, and tools for regression, classification, clustering, and recommendation systems.
- -Familiarity with data visualization tools with Tableau for creating meaningful visualizations.
- -Excellent problem-solving, analytical thinking, and communication skills.
- -Ability to work collaboratively in a team environment and manage multiple priorities effectively.
- -Experience deploying machine-learning models in production environments and monitoring their performance.
- -Knowledge of MLOps practices, model versioning, and automated model deployment pipelines.
- -Familiarity with SQL, NoSQL databases, and data warehousing concepts.
- -Strong understanding of cloud computing principles and architectures.
- -Certifications in AWS, Python, Spark, or related technologies.
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