Data Science Engineer

Overview

Remote
Hybrid
$90 - $95
Contract - W2
Contract - 12 Month(s)

Skills

Python
PyTorch
SQL
Apache Spark
Amazon Web Services
Continuous Integration and Development
Collaboration
Data Collection
Data Engineering
Data Management
Data Science
Java
Keras
Machine Learning (ML)
Scala
Snow Flake Schema
Streaming
Visualization

Job Details

Data Science Engineer with Top Mass Media & Entertainment Company!

Location: Remote anywhere in the USA or Hybrid in New York, California, Washington or Florida

Duration: 12 months

Rate: up to $95.00/HR (W2 ONLY)

 

Job Summary: In this role you will partner with data scientists and engineers to build and deploy large-scale feature sets for, and collaborate on, a machine-learning model.

 

Responsibilities:

feature engineering and optimization: Acquire new data and conform it to usable model features; develop and maintain pipelines using orchestration and data management tools; develop and deploy scalable streaming and batch data pipelines to support petabyte scale datasets for these features.

model development, deployment and optimization: work together with the data scientists and engineers to build and deploy models in large-scale production environments.

 

Best practices: Maintain existing and establish new development, testing, and deployment standards.

 

Collaboration: identify and define opportunities for data collection, feature development, model development, testing, monitoring, and experimentation.

 

Basic qualifications:

-Bachelor s degree in computer science, mathematics, or related fields.

-5+ years of relevant experience

-Experience with data engineering technology and best practices

-Experience with building, training, and deploying machine learning models

-Expertise in Python and SQL

-Expertise in Spark, Snowflake, and dbt

-Experience working in AWS environments

-Experience working with data subject to privacy, governance, and legal policies.

 

Preferred qualifications:

-Proficiency in Databricks and Snowflake in AWS environments

-Experience working in machine learning frameworks such as SparkML, scikit-learn, PyTorch, Keras.

-Experience with Github, Airflow, Scala, and Java

-Proficiency in DevOps and CICD

-Experience with multiple model deployment tools

-Experience with MLflow or other tracking tools

-Experience working with Agile teams

-Experience with data science focused feature stores

-Strong data analysis and visualization skills

-Experience applying mathematical and statistical methods to data

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.