Related skills
sql python pytorch machine learning dbt📋 Description
- Develop and deploy predictive models to identify high-conversion leads.
- Own the full ML lifecycle from data acquisition to deployment.
- Analyze product performance and customer usage to inform roadmap.
- Collaborate with engineering to productionize ML pipelines.
- Build internal analytics, dashboards, and investor insights.
- Prototype, experiment, and iterate quickly with speed and rigor.
🎯 Requirements
- 3–6 years in data science, ML engineering, or analytics roles
- Proficiency in Python, SQL, and ML libraries (scikit-learn, XGBoost, PyTorch)
- Familiarity with data pipelines, model evaluation, deployment workflows
- Independent work in ambiguous contexts with high ownership
- Experience translating messy data into actionable insights
- Bonus: large-scale data, marketing analytics, or tooling (dbt, Airflow)
🎁 Benefits
- Location: San Francisco — In-person 3–4 days per week
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