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Data Scientist - Cambridge, MA (Remote)

Georgia IT, Inc.

Key Facts

Remote From: 
Massachusetts (USA)
Category:  Data Scientist
Full time
Senior (5-10 years)
English

Roles & Responsibilities

  • PhD in a quantitative STEM field with 0–2 years' experience, OR Master's degree with 5–8 years relevant experience
  • Experience delivering data science projects on scientific/engineering datasets
  • Strong communication and collaboration skills
  • Expertise in Python, Pandas, Jupyter, scikit-learn, and machine learning libraries

Requirements:

  • Perform advanced data analysis, visualization, and statistical modeling
  • Apply Bayesian experimental design techniques
  • Develop optimization and simulation solutions including constrained optimization and Monte Carlo simulations
  • Present analytical insights to technical and non-technical audiences

Job description

Title: Data Scientist
Location: Cambridge, MA
Position Type: Contract (06/01/2026 – 12/31/2026)
Rate: DOE

Responsibilities
  • Perform advanced data analysis, visualization, and statistical modeling.
  • Apply Bayesian experimental design techniques.
  • Develop optimization and simulation solutions including:
    • Constrained optimization
    • Machine learning
    • Monte Carlo simulations
  • Solve manufacturing challenges such as:
    • Schedule optimization
    • Batch generation
  • Partner with stakeholders across:
    • Data acquisition
    • Modeling
    • Validation
    • Deployment
    • Monitoring
  • Collaborate with:
    • Data scientists
    • Engineers
    • Statisticians
    • Manufacturing teams
  • Implement best practices for:
    • Scalability
    • Reproducibility
    • Software engineering
  • Present analytical insights to technical and non-technical audiences.
  • Integrate Generative AI capabilities into workflows and experimentation.
Required Qualifications
  • PhD in a quantitative STEM field with 0–2 years' experience, OR
  • Master's degree with 5–8 years relevant experience.
  • Experience delivering data science projects on scientific/engineering datasets.
  • Strong communication and collaboration skills.
  • Expertise in:
    • Python
    • Pandas
    • Jupyter
    • scikit-learn
    • Machine learning libraries
  • Familiarity with:
    • AWS
    • Docker
    • Git
    • PostgreSQL
  • Experience handling large and unstructured datasets.
  • Ability to manage multiple projects in dynamic environments.
  • English proficiency required.
  • Optimization and bioinformatics experience preferred.
Key Responsibilities
  • Build and tune supervised and unsupervised ML models for anomaly detection.
  • Monitor real-time data streams and system logs.
  • Analyze complex datasets to identify root causes of anomalies.
  • Optimize alert systems to minimize false positives.
  • Develop automated pipelines for:
    • Data quality
    • Security
    • Detection systems
  • Work closely with product management, IT, and data engineering teams.
  • Apply:
    • Statistical analysis
    • Data mining
    • Feature engineering techniques.
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