Data Scientist

What the role involves

• Design experiments and analyses that answer open-ended business questions
• Build, validate and document predictive and causal models
• Quantify uncertainty and communicate model limitations honestly
• Partner with engineers to move models from analysis into production
• Review analyses for methodology, bias and unintended consequences

Core skills

• Statistical Analysis (level 5/5)
• Python for Data Analysis (level 4/5)
• SQL (level 4/5)
• Experimental Design & A/B Testing (level 4/5)
• Machine Learning Fundamentals (level 4/5)
• Data Visualization & Communication (level 4/5)

Preferred skills

• Causal Inference
• Bayesian Methods
• Deep Learning (PyTorch)
• Stakeholder Management

Tools

Experience expected

2-5 years in applied statistics, quantitative research or modelling

Projects that prove the role

• Causal impact study of a pricing change with credible-control design
• Forecasting model with documented backtesting and error analysis
• Churn propensity model that changed a retention budget decision

Evidence to collect

• A written analysis with assumptions, uncertainty and limitations stated
• A reproducible notebook or repository others can rerun
• A model card describing intended use and failure modes

What the interview covers

• Designing an experiment with a difficult metric or a small sample
• Explaining when a correlation is not causal
• Validating a model without leaking future information
• Communicating a null or negative result to a business audience

How the role progresses

• Data Analyst
• Data Scientist
• Senior Data Scientist
• Principal Data Scientist
• Head of Data Science

Certifications that carry weight

• Google Data Analytics Professional Certificate
• IBM Data Science Professional Certificate

Related roles

• data-analyst
• ai-ml-engineer
• analytics-engineer

Turn this into a plan

Inside CareerDev4AI, choosing this role generates a roadmap of the skills, projects and milestones that move you towards it.