Senior ML Engineer, Pricing Systems

“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.”

About Walkway

Walkway builds AI-driven revenue intelligence for the tours & activities industry. We help operators grow through dynamic pricing, competitive benchmarks, and data-rich insights. Our stack is GCP-centric and data heavy (real-time + batch).

The Role

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.

What you’ll do Pricing Science & Modeling

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.

Define KPIs (revenue / seat, conversion, occupancy, margin) and attribution logic; build offline / online evaluation, backtests, and simulation / sandbox environments.

Partner closely with Product to keep price recommendations explainable and operator-friendly.

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.

You treat models as products, you design APIs and batch jobs that other services depend on.

Implement privacy and security best practices (PII handling, access control, auditability).

Leadership & Collaboration

Co-lead the pricing roadmap; break down research into shippable increments.

Mentor data scientists / engineers; set standards for code, reviews, docs, and experiment hygiene.

Work cross-functionally with Backend, Integrations, and Design; communicate clearly with non-technical stakeholders.

What you’ve shipped / Requirements 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 ; comfort profiling & optimizing code / queries.

Proven data engineering chops : building production pipelines / orchestration (dbt, Airflow / Mage), data modeling, testing, monitoring, and cost / perf tuning.

Depth in time-series forecasting , elasticity / choice models , causal inference or uplift , and experiment design.

Experience deploying models / services on GCP (or AWS / Azure and willing to pivot) : BigQuery, Cloud Run, Pub / Sub, Vertex AI / MLFlow, Cloud Functions / Scheduler. Evidence of taking a model from notebook to production service with clear SLOs, versioned rollouts, and post-incident learnings.

Comfortable with MLOps : model registry, CI / CD for ML, drift / quality monitoring, feature stores, reproducibility.

Excellent communication; can turn ambiguity into a plan and explain trade-offs to product & customers.

Bonus : Prior project or team leadership (tech lead / manager or de-facto lead on large initiatives).

Nice to have

OTA / travel tech integrations, pricing under parity and channel constraints.

Reinforcement learning / contextual bandits in production.

DuckDB, Spark / Beam, Redis, Kafka

Experience designing explainable pricing UIs and operator-facing levers (guardrails, sensitivity sliders, override workflows).

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.

Why Walkway Own the pricing engine of an award-winning AI product used by real operators.

Ship research to prod quickly with a pragmatic, low-ego team.

Influence product, architecture, and the roadmap; opportunity to build & lead a small pricing science group.

Remote-first with EU and US overlap, periodic in-person meetups for planning and connection, travel covered

How to apply

Please apply here, or email me at emmanuel@walkway.ai, optionally with :

LinkedIn / GitHub and a short note on a pricing system you designed & deployed (objective, method, stack, results, lessons).

Any links to papers, write-ups, or dashboards you can share.

Job Title : Senior Data Scientist (Pricing), Senior ML Engineer, Pricing Systems, Senior Pricing Scientist, ML Engineering, Senior Applied Scientist (Pricing)