Data Scientist AI · Full-time

Sopsai

Greater London

On-site

GBP 60,000 - 80,000

Full time

14 days+

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Job summary

Sopsai is seeking a Machine Learning Engineer in Greater London to frame, model and ship ML solutions that drive client profitability. You will translate business challenges into modelable solutions and deploy advanced ML algorithms.

Ideal candidates will have 4+ years in data science, robust skills in Python and SQL, and familiarity with MLOps. Experience in financial services or related domains is a plus. Send your CV and a short note about your proudest work.

Qualifications

  • 4+ years applied data science experience with production deployments.
  • Strong background in Python and SQL.
  • Solid understanding of statistical methods and experimentation.

Responsibilities

  • Translate ambiguous business problems into modelable formulations.
  • Build, evaluate and deploy classical ML and modern LLM solutions.
  • Design experiments and causal analyses to quantify impact.
  • Own model monitoring, drift detection and lifecycle in production.
  • Communicate insights to executive stakeholders.

Skills

Python (pandas, scikit-learn, PyTorch)
SQL
Statistics and causal inference
MLOps stack experience (MLflow, SageMaker, Vertex)

Job description

Frame, model and ship ML solutions that move client P&L.

What you'll do
  • Translate ambiguous business problems into modelable formulations
  • Build, evaluate and ship classical ML and modern LLM solutions
  • Design experiments and causal analyses to quantify impact
  • Own model monitoring, drift detection and lifecycle in production
  • Communicate insights to executive stakeholders with clarity
What you bring
  • 4+ years applied data science with production deployments
  • Strong Python (pandas, scikit-learn, PyTorch) and SQL
  • Solid grounding in statistics, experimentation and causal inference
  • Experience with at least one MLOps stack (MLflow, SageMaker, Vertex)
Nice to have
  • Published research or Kaggle competition experience
  • Domain depth in financial services, retail or healthcare

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