Entry Level Data Scientist / ML Engineer - AI & Analytic

CapgeminiSeattle, WA
1d$65,000 - $75,000

About The Position

The Data Scientist / ML Engineer will demonstrate excellent knowledge of ML algorithms (e.g., Linear Regression, Logistic Regression, Clustering/Segmentation, Decision Tree, Random Forest, GBM, DNN, Naive Bayes, Support Vector Machine, etc.) to lead efforts, teams, projects, and engage with customers. Responsible for developing and implementing AI-assisted marketing analytics solutions that address customer needs using data science and machine learning. Work closely with multi-functional teams to deliver innovative solutions that drive business growth and improve customer engagement.

Requirements

  • Excellent knowledge of ML algorithms (e.g., Linear Regression, Logistic Regression, Clustering/Segmentation, Decision Tree, Random Forest, GBM, DNN, Naive Bayes, Support Vector Machine, etc.)

Responsibilities

  • Design, implement, and optimize machine learning models (supervised, unsupervised, and reinforcement learning).
  • Work on projects involving NLP, computer vision, recommendation systems, and predictive analytics.
  • Perform feature engineering, data preprocessing, and model selection.
  • Collaborate with Data Engineers to acquire and preprocess large datasets.
  • Build and maintain data pipelines to support model training, testing, and deployment.
  • Ensure data quality, consistency, and reliability.
  • Deploy ML models into production environments using CI/CD and MLOps practices.
  • Monitor model performance, retrain models, and manage model versioning.
  • Optimize inference performance and resource utilization.
  • Stay current with emerging ML/AI technologies, frameworks, and research.
  • Evaluate new algorithms, tools, and libraries to improve model performance.
  • Experiment with novel approaches to solve complex business problems.
  • Work with software engineers, data scientists, and product managers to integrate ML solutions into applications.
  • Mentor junior engineers and share best practices in ML development and deployment.

Benefits

  • Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave
  • Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)
  • Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
  • Life and disability insurance
  • Employee assistance programs
  • Other benefits as provided by local policy and eligibility

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What This Job Offers

Job Type

Full-time

Career Level

Entry Level

Education Level

No Education Listed

Number of Employees

5,001-10,000 employees

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