Senior Data Scientist

Senior Data Scientist

Posted 1 week ago by Integration Architects

Negotiable
Undetermined
Remote
Remote

Summary: The Senior Data Scientist role at Integration Architects focuses on transforming enterprise data into actionable models and insights that inform business decisions. This position requires a strong background in data science and machine learning, with responsibilities including model deployment and statistical analysis. The role is remote and offers a contract type of C2C or W2. Candidates should have extensive experience in data science and a solid understanding of statistical methods.

Key Responsibilities:

  • Frame business problems as data science problems and design the approach
  • Build, validate, and deploy ML models into production
  • Run statistical analysis and experimentation (A/B, causal)
  • Collaborate with data engineering to productionize features and pipelines
  • Communicate findings clearly to non-technical stakeholders

Key Skills:

  • 12+ years in data science / applied ML
  • Strong Python (pandas, scikit-learn) and SQL
  • Production ML deployment experience, not just notebooks
  • Solid grounding in statistics and experimental design
  • Cloud ML tooling (SageMaker, Azure ML, Vertex, or similar)

Salary (Rate): undetermined

City: undetermined

Country: undetermined

Working Arrangements: remote

IR35 Status: undetermined

Seniority Level: undetermined

Industry: IT

Detailed Description From Employer:

Location: Remote (U.S.) | Type: Contract (C2C or W2)

Integration Architects seeks a Senior Data Scientist to turn enterprise data into models and insight that drive real business decisions.

What you''''''''ll do

  • Frame business problems as data science problems and design the approach
  • Build, validate, and deploy ML models into production
  • Run statistical analysis and experimentation (A/B, causal)
  • Collaborate with data engineering to productionize features and pipelines
  • Communicate findings clearly to non-technical stakeholders

What you bring

  • 12+ years in data science / applied ML
  • Strong Python (pandas, scikit-learn) and SQL
  • Production ML deployment experience, not just notebooks
  • Solid grounding in statistics and experimental design
  • Cloud ML tooling (SageMaker, Azure ML, Vertex, or similar)