Own pricing science end to end, from elasticity and demand modeling to shipping and monitoring models on GCP, with clear guardrails and operator-friendly explainability.”
We help operators grow through dynamic pricing, competitive benchmarks, and data-rich insights. Our stack is GCP-centric and data heavy (real-time + batch).
We’re hiring a Senior Data Scientist specialized in Pricing who is also excellent at data engineering. You’ll co-own the pricing science roadmap end-to-end from demand/elasticity modeling to production deployment and monitoring - and help shape product and platform decisions with the founders. This is a hands-on, high-impact role with the opportunity to lead projects and people.
We’re a US-based company; this position is a remote contractor role with strong overlap to EU/US time zones.
Design the pricing methodology for multiple channels (direct + OTAs): demand forecasting, price elasticity estimation, competitor response, inventory/lead-time effects, seasonality & events.
Build hybrid rules + ML systems that start simple (guardrails, explainability) and graduate to Bayesian/causal, RL/bandit approaches where appropriate.
build offline/online evaluation, backtests, and simulation/sandbox environments.
MLOps & Data Engineering
Own feature pipelines and model services on GCP : BigQuery, Cloud Run, Pub/Sub, Cloud Storage, Vertex AI (or MLFlow), dbt/Mage/Airflow.
Build reliable ELT/ETL (schema design, data contracts, idempotency, SLAs), feature stores, and model registries.
Ship models to production with CI/CD, canary/A-B rollouts, monitoring for drift/quality, and automated re-training schedules.
Implement privacy and security best practices (PII handling, access control, auditability).
Mentor data scientists/engineers; Work cross-functionally with Backend, Integrations, and Design; 7+ years in Data Science/ML with dynamic pricing / revenue management in adjacent spaces (travel, hospitality, mobility, e-commerce, marketplaces, ads, or gig platforms).
~ Strong Python (pandas, numpy, scikit-learn; PyTorch/TensorFlow a plus) and SQL ; Proven data engineering chops: building production pipelines/orchestration (dbt, Airflow/Mage), data modeling, testing, monitoring, and cost/perf tuning.
~ Experience deploying models/services on GCP (or AWS/Azure and willing to pivot): BigQuery, Cloud Run, Pub/Sub, Vertex AI/MLFlow, Cloud Functions/Scheduler. Comfortable with MLOps: model registry, CI/CD for ML, drift/quality monitoring, feature stores, reproducibility.
~ Prior project or team leadership (tech lead/manager or de-facto lead on large initiatives).
DuckDB, Spark/Beam, Redis, Kafka
Our stack (you’ll influence it) GCP (BigQuery, Cloud Run, Pub/Sub, Storage, Scheduler, Vertex AI), Python, dbt, Mage/Airflow, Postgres, DuckDB, GitHub Actions, Sentry, Next.js.
Remote-first with EU and US overlap, periodic in-person meetups for planning and connection, travel covered
LinkedIn/GitHub and a short note on a pricing system you designed & deployed (objective, method, stack, results, lessons).
Job Title: Senior Data Scientist (Pricing), Senior ML Engineer, Pricing Systems, Senior Pricing Scientist, ML Engineering, Senior Applied Scientist (Pricing)