Data Science Engineer

Randstad is partnering with a firm to hire a contract Data Science Engineer 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 crossfunctional teams to extract actionable insights from data and drive business outcomes.

Responsibilities:

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.

Qualifications:

Bachelors 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 56 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 problemsolving analytical thinking and communication skills.

Ability to work collaboratively in a team environment and manage multiple priorities effectively.

Experience deploying machinelearning 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.