Senior ML Engineer, Pricing Systems

Walkway; Ibiza; A distancia; EUR 70.000 - 90.000; Jornada completa

Descripción de la vacante

An innovative AI company is seeking a Senior Data Scientist specializing in Pricing to oversee the pricing science roadmap. This role involves deep engagement with data engineering, dynamic pricing methodologies, and leading projects remotely. The suitable candidate will have significant experience in data science, strong Python and SQL skills, and proficiency in GCP, with responsibilities including production deployment and cross-team collaboration. An exciting opportunity for someone ready to make an impact!

Servicios

Remote-first work environment

Opportunity to influence product and architecture

Periodic in-person meetups covered by the company

Formación

• 7+ years in Data Science / ML with dynamic pricing experience.
• Experience deploying models on GCP or AWS/Azure.
• Ability to communicate technical ideas effectively.

Responsabilidades

• Own pricing science end to end, from modeling to monitoring.
• Build reliable ELT/ETL pipelines and ship models to production.
• Mentor junior data scientists and lead cross-functional collaboration.

Conocimientos

Strong Python

Data Engineering

Elasticity modeling

Machine Learning

SQL

Time-series forecasting

Excellent communication

Herramientas

GCP

BigQuery

Cloud Run

dbt

Airflow

Vertex AI

Descripción del empleo

“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 [e-mail], 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)