happyhotel

15 сен

Machine Learning Engineer

ориентир по рынку

вакансия зп не указана

в среднем 292 674 ₽

мэтч

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Рекламный баннер: ОБЩЕСТВО С ОГРАНИЧЕННОЙ ОТВЕТСТВЕННОСТЬЮ "ЦЕНТР НАЦИОНАЛЬНЫХ ИНТЕЛЛЕКТУАЛЬНЫХ СИСТЕМ"

описание

Описания нет

задачи

As a Senior Machine Learning Engineer, you will work in the Pricing & Revenue context, focusing on data-driven improvements for forecasting, pricing logic, and product insights. You will develop analyses and models that demonstrate measurable impact in our product – with thorough evaluation, a solid data foundation, and pragmatic implementation. You will collaborate closely with Product & Engineering.

Model Evolution: You will develop and optimize our forecasting and pricing models as well as data-driven decision logics, always with methodical pragmatism and a strong focus on impact.

Signal Hunting: You will work with time series, demand signals, and heterogeneous data sources. You define features and labels carefully to leave no chance for leakage.

Measurement & Guardrails: You are responsible for evaluation through backtesting, robust metrics, and segmentation. You support holdouts and A/B logics and maintain the balance between offline and online performance.

ML Engineering Best Practices: You raise standards for backtesting, reproducibility, and versioning. For us, it's: Engineering quality instead of notebook-only.

Data Visibility: You enhance dashboards and reports that make model and business KPIs transparent. Your focus is always on the highest data quality.

Smart Workflows: You drive reproducible workflows (versioning, clear pipelines, meaningful tests) and automate recurring analyses and evaluation runs.

требования

Track Record: You have 4+ years of experience in data science or applied ML engineering – ideally directly in a product or business context.

Data Intuition: You possess extremely strong SQL skills and a deep sense for data quality, debugging, and consistent metrics.

Python Pro: Your Python code is clean and your analyses are transparent. Initial experience with product-oriented setups is a big plus.

Experiment Mindset: You master the basics of bias/leakage-awareness and know how to think in guardrails and offline-vs-online scenarios.

Work Style: You take full ownership of your topics. You work according to the 80/20 principle (pragmatic!), are reliable, and communicate clearly.

Entrepreneurial Spirit: You think entrepreneurially and want to truly make a difference.

Language Skills: You communicate fluently and confidently in English.

Nice-to-haves – What Sets the Best Apart

Domain Expertise: You already have experience in revenue management or dynamic pricing (e.g., hotel, travel, eCommerce, or mobility).

Demand Knowledge: You are familiar with seasonality, events, lead times, and segment patterns.

Modern Stack: You have already worked with analytics engineering or warehouse tools such as dbt, Snowflake, or Met

Hands-On MLOps & Cloud: Bonus if you have hands-on skills to work with MLOps tooling and cloud infrastructure, e.g. AWS

условия

Условий нет

навыки

sql python dbt snowflake mlops aws

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