Senior Data Scientist — ML Pipelines on AWS (Hybrid)

ManpowerGroup Global, Inc.

Charlotte (NC)

Hybrid

USD 120,000 - 180,000

Full time

3 days ago
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Benefits offered by this job

Innovative projects
Diverse team
Skill development
Impactful solutions
Growth opportunities

Job summary

ManpowerGroup Global, Inc. seeks a Senior Data Scientist in Charlotte, NC, on a hybrid basis. You will design and implement end-to-end ML pipelines leveraging AWS services, and work across data analytics teams to deliver data-driven insights.

You will develop predictive models using Python or R, perform data cleaning and feature engineering, and collaborate with data engineers on ETL pipelines to ensure robust data availability and reliability.

Qualifications

  • Experience designing and implementing ML pipelines on cloud platforms, especially AWS.
  • Proficiency in Python, R, or similar data science tools.
  • Familiarity with AWS analytics services such as Athena, Redshift, QuickSight, EMR.
  • Strong data collection, cleaning and feature engineering skills.
  • Ability to translate business objectives into data science solutions.

Responsibilities

  • Design and implement end-to-end ML pipelines using AWS services (SageMaker, AWS Glue, Lambda, S3).
  • Perform data collection, cleaning, and feature engineering for modeling datasets.
  • Develop predictive models and statistical analyses with Python, R, or similar tools.
  • Deploy, monitor, and optimize ML models in production following AWS ML Ops best practices.
  • Collaborate with data engineers to design ETL pipelines ensuring data availability and reliability.

Job description

ManpowerGroup Global, Inc. seeks a Senior Data Scientist in Charlotte, NC, on a hybrid basis. You will design and implement end-to-end ML pipelines leveraging AWS services, and work across data analytics teams to deliver data-driven insights.

You will develop predictive models using Python or R, perform data cleaning and feature engineering, and collaborate with data engineers on ETL pipelines to ensure robust data availability and reliability.

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