- Company Name
- SuperAwesome
- Job Title
- Data Scientist
- Job Description
-
**Job Title:** Data Scientist
**Role Summary:**
Design, develop, and maintain production‑ready machine‑learning models that optimize programmatic ad bidding, content moderation, audience categorisation, and campaign performance for youth‑focused digital advertising. Collaborate with product, engineering, and analytics teams to translate business problems into data‑driven solutions while ensuring privacy compliance and safety standards.
**Expectations:**
- Deliver robust, scalable ML solutions that meet defined business objectives.
- Communicate technical concepts clearly to cross‑functional stakeholders.
- Maintain high code quality, documentation, and model monitoring.
- Stay current with emerging ML techniques, especially in Bayesian, causal inference, and LLM applications.
**Key Responsibilities:**
- Partner with product, engineering, and end‑users to define problem statements and success metrics.
- Develop and deploy models for auction bid optimisation, content safety, audience clustering, and advertising performance prediction.
- Perform data extraction, cleaning, and feature engineering using Python, Pandas, NumPy, and SQL.
- Test, validate, and monitor models in production; implement alerts and performance dashboards.
- Document model pipelines, create APIs (e.g., FastAPI), and manage version control (Git).
- Contribute to MLOps practices, including CI/CD, containerisation, and cloud deployment (AWS preferred).
**Required Skills:**
- Proficient in Python (incl. Pandas, NumPy, Scikit‑learn).
- Strong SQL writing and query optimisation.
- Solid understanding of statistical modelling and standard ML algorithms.
- Experience with full ML lifecycle: data prep, modelling, validation, deployment, monitoring.
- Ability to explain technical work to non‑technical audiences.
**Nice‑to‑Have Skills:**
- Advanced mathematics, Bayesian modelling, causal inference.
- Experience with LLM fine‑tuning, prompt engineering, or other generative AI tools.
- Big‑data processing (e.g., PySpark).
- Adtech/Martech domain knowledge, survey data analysis, brand‑lift studies.
- Cloud platforms (AWS), MLOps tooling, API development, Jira, GitHub.
**Required Education & Certifications:**
- Bachelor’s degree in a quantitative field (e.g., Computer Science, Statistics, Mathematics, Economics, Physics) or equivalent practical experience.
- Advanced degree (MSc/PhD) is a plus but not mandatory.