Senior Data Scientist

ManpowerGroup Global, Inc.; Charlotte (NC); Hybrid; USD 120,000 - 180,000; Full time

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

Our client, a leading organization in the industry, is seeking a Senior Data Scientist to join their team. As a Senior Data Scientist, you will be part of the Data Analytics Department supporting various project teams.

Job Title:

Senior Data Scientist

Location:

Charlotte, NC / Hybrid

What's the Job?

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

What's Needed?

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

What's in it for me?

• Opportunity to work on innovative projects with cutting-edge cloud technologies
• Collaborate with a diverse and talented team of professionals
• Enhance your skills in machine learning, data analytics, and cloud computing
• Contribute to impactful solutions that drive business success
• Be part of a forward-thinking organization committed to professional growth