Data Scientist

5+ years in applied data science, with significant experience on commercial problems (churn, LTV, propensity, attribution, pricing, or similar).

Strong SQL and Python (pandas, scikit-learn, statsmodels). Comfortable building production-grade code, not just notebooks.

Hands-on experience with Snowflake (or a comparable cloud data warehouse — BigQuery, Redshift, Databricks).

Experience deploying models on AWS (SageMaker, Lambda, ECS, or similar).

Solid grounding in statistics, experimentation, and causal inference — you know when a correlation isn't enough.

Track record of shipping models that are actually used by the business, not just built.

Excellent communication — you can explain a model to a CFO and debug a feature pipeline with an engineer in the same afternoon.

Nice-to-have

Experience with n8n or other workflow automation tools (Airflow, Prefect, Dagster).

Exposure to payments, fintech, SaaS, or other recurring-revenue businesses.

DBT experience for analytics engineering.

Experience integrating LLMs or GenAI into commercial workflows.

Planet is an equal opportunity employer where diversity is valued, and all employment is decided based on qualifications, merit, and business need.

Come and grow your career in the most exciting, fast paced technology market, with a business that delivers feel-good connected commerce.

We would love to hear from you – Apply now .

At Planet, we embrace a hybrid work model, with three days a week in the office.

Reasonable accommodations may be made in order to allow for an individual to perform the essential functions of this role successfully.