Senior Optimization Data Scientist - ML on GCP & MLOps

RPS Softwares AB

Town of Sweden (NY)

On-site

USD 93,150 - 134,550

Full time

14 days+
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Job summary

RPS Softwares AB in Sweden seeks an experienced Senior Optimization Data Scientist to design and maintain production-grade optimization models and ML solutions on Google Cloud Platform (GCP). You will build scalable data pipelines, implement MLOps practices, and work with cross-functional teams to translate business needs into technical outcomes.

The role requires 4–9 years in Data Science, Optimization, or Operations Research, strong Python skills, and proficiency in SQL.

Qualifications

  • 4–9 years of experience in Data Science, Optimization, or Operations Research.
  • Strong Python programming skills and production-ready coding.
  • Hands-on experience deploying ML solutions on Google Cloud Platform (GCP).
  • Experience with MLOps, CI/CD pipelines, and production model lifecycle management.
  • Advanced SQL skills for data analysis.

Responsibilities

  • Design, optimize, and maintain production-grade Linear and Mixed Integer Programming models and ML solutions on GCP.
  • Build scalable data integration pipelines and implement robust MLOps practices (CI/CD, deployment, lifecycle monitoring).
  • Translate business requirements into technical solutions and present insights to stakeholders.

Skills

Python
Data Science
Optimization
Operations Research
GCP

Education

Bachelor's degree in Computer Science or related field

Tools

Google Cloud Platform (GCP)
CI/CD

Job description

RPS Softwares AB in Sweden seeks an experienced Senior Optimization Data Scientist to design and maintain production-grade optimization models and ML solutions on Google Cloud Platform (GCP). You will build scalable data pipelines, implement MLOps practices, and work with cross-functional teams to translate business needs into technical outcomes.

The role requires 4–9 years in Data Science, Optimization, or Operations Research, strong Python skills, and proficiency in SQL.

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