Data Scientist - W2 Only

Brilliant

Fort Worth, TX, United States

3 days ago

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Role details

Contract type

Contract

Employment type

Full-time (> 32 hours)

Experience level

Experienced

Experience required

3 years minimum

Working hours

Regular working hours

Job source

www.dice.com

Tech stack

Microsoft Azure Big Data Data Mining Data Visualization Software Debugging Distributed Systems Python (Programming Language) Machine Learning Performance Tuning Power BI Standard Sql Systems Integration

+9 more

Tableau (Software) Feature Engineering Apache Spark Parallel Computation Information Technology Production Code Machine Learning Operations Code Restructuring Databricks

Job description

Develop, refactor, test, and optimize production-quality Python code for machine learning applications.
Design, build, deploy, and maintain machine learning models and pipelines.
Productionize ML workflows, including model deployment, orchestration, monitoring, optimization, and troubleshooting.
Extract, clean, transform, and analyze large datasets to support business and customer intelligence initiatives.
Apply statistical methods, machine learning techniques, and feature engineering to improve model performance.
Work with data scientists, data engineers, product partners, and business stakeholders to deliver scalable ML solutions.
Improve existing codebases, pipelines, and system integrations for reliability, maintainability, and performance.
Debug technical issues and conduct performance tuning across the ML lifecycle.
Use cloud platforms and parallel-processing technologies to scale model development and deployment.
Document technical solutions and communicate findings clearly to both technical and non-technical audiences.
Support quality, innovation, scalability, and measurable business or revenue impact across the organization.

Requirements

Master’s or PhD degree in Data Science, Computer Science, Statistics, Applied Mathematics, Machine Learning, or a related quantitative field.
At least 3 years of relevant professional experience.
Strong hands-on experience with Python programming.
Experience writing modular, testable, maintainable, and production-grade code.
Practical experience with data extraction, cleaning, transformation, and analysis.
Strong understanding of statistical and machine learning techniques.
Hands-on experience developing and productionizing machine learning pipelines. Preferred:
8+ years of experience in a technical professional environment.
Experience with Databricks and Spark-based machine learning pipelines.
Experience deploying machine learning models to production environments.
Experience with ML orchestration, monitoring, and optimization.
Knowledge of SQL and experience working with large-scale datasets.
Experience with ML lifecycle tools such as MLflow, CI/CD pipelines, and model-monitoring platforms.
Experience with Azure or other cloud platforms.
Experience with parallel processing and distributed computing.
Experience creating dashboards or data visualizations using Tableau or Power BI.
Airline or transportation industry experience.

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