What you will be doing Artefact is looking for a Senior AI & Data Scientist: a scientist who owns models end to end, from problem framing through production.
You will work across the full modeling spectrum - forecasting, classification, clustering, and causal analysis on one engagement; fine-tuning experiments and LLM evaluation on the next. You will own your models: the data behind them, the methodology, the deployment, and the story told to the client. You will also help junior scientists grow.
- Translate business and marketing challenges into analytical use cases with clear hypotheses and success metrics.
- Develop statistical and machine learning models: regression, forecasting, classification, clustering, and causal inference.
- Select techniques based on business context, constraints, and data availability - and be able to justify the choice.
- Ship production-ready solutions: training, deployment, monitoring, and ongoing refinement.
- Run fine-tuning experiments: dataset curation, SFT, LoRA/PEFT, and rigorous evaluation of results against baselines.
- Build evaluation suites for LLM systems: benchmarks, LLM-as-judge patterns, and regression tests.
- Work with embeddings and retrieval where they affect answer quality.
- Contribute to model selection decisions: prompting vs. RAG vs. fine-tuning, cost vs. quality vs. latency.
- Build data pipelines for ingestion, transformation, and quality assurance across diverse data sources.
- Create clear visualizations and dashboards that support data storytelling and decision making.
- Present findings to client stakeholders, translating methodology into business language.
- Mentor junior data scientists and use AI-assisted tools (Claude Code, Gemini CLI) to raise the whole team's pace.
What we are looking for - 3-5 years of relevant data science experience with a substantial quantitative skill set.
- Strong knowledge of statistics and ML algorithms, with at least one proven experience developing and deploying models.
- Proficiency in Python (scikit-learn, XGBoost; PyTorch a strong plus) and solid SQL.
- Hands-on experience with LLMs: evaluation, RAG, or fine-tuning experiments (professional or substantial personal projects).
- Specialization in at least one major AI platform ecosystem - Google (Gemini, Vertex AI), Anthropic (Claude), or OpenAI - and familiarity with a cloud platform (GCP, Azure, or AWS).
- Comfort with AI-assisted development tools such as Claude Code, Gemini CLI, or Cursor.
- Excellent interpersonal and communication skills: you can present methodology and results to non-technical audiences.
- Master's degree (or higher) in statistics/mathematics, engineering, computer science, economics, or a related field, or equivalent experience.
Preferred:- Causal inference, time series, or advanced statistics experience.
- Hugging Face Transformers, LoRA/PEFT, or open-weight model experience.
- MLOps exposure: model versioning, pipelines, monitoring.
- Cloud certifications, especially Google Cloud Professional Machine Learning Engineer.
