Senior Data Scientist

AgileEngine, LLC
McLean, United States of America
yesterday

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior

Job location

Remote
McLean, United States of America

Tech stack

Agile Methodologies
Artificial Intelligence
Airflow
Amazon Web Services (AWS)
Data analysis
Cloud Computing
Python
Machine Learning
Azure
Software Deployment
Feature Engineering
Sql Optimization
Large Language Models
Snowflake
GIT
Machine Learning Operations
Data Pipelines

Job description

We are looking for a Senior Data Scientist to develop, deploy, and maintain production machine learning models in a cloud-native enterprise environment. You will build and improve data pipelines supporting ML workflows, perform exploratory data analysis and feature engineering, and collaborate with engineering and business stakeholders to deliver scalable ML solutions using AWS SageMaker or equivalent enterprise ML platforms. The role requires 4+ years of production ML experience with strong Python and advanced SQL skills, and includes contribution to AI and LLM-based capabilities where applicable.

What you will do

  • Develop, deploy, and maintain production machine learning models.
  • Perform exploratory data analysis and feature engineering.
  • Build and improve data pipelines that support ML workflows.
  • Collaborate with engineering and business stakeholders to deliver scalable ML solutions.
  • Contribute to AI/LLM-based capabilities where applicable.

Requirements

  • 4+ years of experience building and maintaining production machine learning models.
  • Strong Python programming skills.
  • Experience with AWS SageMaker or another enterprise ML platform, such as Vertex AI or Azure ML, supporting production ML pipelines.
  • Experience deploying and monitoring ML models in production, not only notebook-based development.
  • Advanced SQL skills.
  • Git and version control experience.
  • Experience working independently in production environments.
  • Experience building scalable ML solutions in enterprise environments.
  • Familiarity with cloud-based ML platforms and production deployment best practices.
  • Strong communication skills and the ability to work with cross-functional teams.

Nice to haves

  • Experience with MLOps tools such as MLflow, Airflow, dbt, or similar.
  • Experience with Snowflake.
  • Marketing, growth, experimentation, or causal inference experience.
  • Experience with LLMs or AI agents.
  • Familiarity with Agile development practices.

Benefits & conditions

Accelerate your professional journey with mentorship, TechTalks, and personalized growth roadmaps

  • Competitive compensation

We match your ever-growing skills, talent, and contributions with competitive USD-based compensation and budgets for education, fitness, and team activities

  • A selection of exciting projects

Join projects with modern solutions development and top-tier clients that include Fortune 500 enterprises and leading product brands

  • Flextime

Tailor your schedule for an optimal work-life balance, by having the options of working from home and going to the office - whatever makes you the happiest and most productive.

About the company

About AgileEngine 201-500

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