- Engage with the business objectives behind key tasks: pricing for B2B/B2C, forecasting and optimization of financial and operational metrics, incident prioritization, and improving customer journey efficiency (revenue growth, cost savings, business impact).
- Drive ML projects end-to-end: from problem definition and formalization to modeling, piloting, and presenting results.
- Collaborate with data engineers to collect the necessary datasets and assess implementation feasibility.
- Work with analysts on A/B test design: defining metrics, splits, and interpreting results.
- Develop models (classic ML and DL, time series, uplift modeling), conduct error analysis and performance evaluation.
- Prepare models and code for transfer to production infrastructure (deployment and releases handled by the technical team).
- Take ownership of model quality, monitor key metrics, and collaborate with the team on degradation issues and improvement plans.
Requirements
- 3+ years of experience as a Data Scientist.
- Proven experience with end-to-end ML projects (ability to oversee the entire process).
- Strong knowledge of classical machine learning techniques (feature engineering, classification, regression, boosting, etc.).
- Hands-on experience with uplift modeling and time series tasks (with real business applications).
- Experience working with business stakeholders and understanding optimization problems: pricing, B2C, LTV, retention, AB testing, and more.
- Proficient in Python for DS/ML (writing clean, readable code for models and experiments).
- Confident SQL user (able to build datasets, write joins, and perform data analysis).
- Nice to have: experience with MLflow/DVC, pipelines (Airflow or similar), anomaly detection/anti-fraud, deep learning (PyTorch/TensorFlow), and model monitoring.
Benefits
- A fully flexible work schedule — there’s no pressure to start work at exactly 9:00 AM; what matters is achieving results and moving forward;
- Each person in our team is encouraged to choose their preferred work format. You can work fully remotely, come to the office, or choose a hybrid work model;
- We are an ambitious and supportive team who love what they do, appreciate each other, and grow together;
- The growth and development of each employee is our priority, so we have internal programs available for adaptation and training, development of soft skills and leadership abilities that are tailored individually to each employee;
- We also provide partial compensation for employees participating in external training and conferences;
- In tourism, it's difficult to grow without an excellent knowledge of English, and we support our employees' language learning goals — we organize group and individual lessons, plus speaking clubs with colleagues from all over the world;
- And, of course, to encourage you to travel more, we offer corporate prices on hotels and other travel services;
- We prioritize well-being and are committed to supporting the overall health and work-life balance at ETG. As part of this commitment, we provide MyTime Day Off - an extra day off that is designed to give our employees the flexibility to focus on important matters, whether it’s taking care of their health, mental recharge, addressing personal issues, or any other important activities.
Learn more about our data protection practices in our Privacy Policy: https://emergingtravel.notion.site/recruitment-privacy-notice
Skills Required
- 3+ years of experience as a Data Scientist
- Experience with end-to-end machine learning projects
- Strong knowledge of classical machine learning techniques, including feature engineering, classification, regression, and boosting
- Hands-on experience with uplift modeling and time series tasks applied to real business problems
- Experience working with business stakeholders and optimization problems such as pricing, B2C, LTV, retention, and A/B testing
- Proficiency in Python for data science and machine learning
- Confident SQL skills, including dataset creation, joins, and data analysis
- Experience with MLflow or DVC
- Experience with Airflow or similar data and machine learning pipelines
- Experience with anomaly detection or anti-fraud
- Experience with deep learning using PyTorch or TensorFlow
- Experience with model monitoring
Emerging Travel Group Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Emerging Travel Group and has not been reviewed or approved by Emerging Travel Group.
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Wellbeing & Lifestyle Benefits — Remote-first arrangements and flexible schedules are highlighted across brands, and corporate prices on hotels and other travel services provide an industry-specific perk. Learning supports such as a corporate English school and partial reimbursement for courses and conferences complement the lifestyle-oriented package.
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Leave & Time Off Breadth — An extra paid “MyTime Day Off” once per quarter is described to support work–life balance. Generous PTO, paid sick days, and paid holidays are also referenced on third‑party listings.
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Healthcare Strength — In the U.S., health insurance with HSA options is described as available for some employees.
Emerging Travel Group Insights
What We Do
Emerging Travel is an online travel group based in Delaware, USA. The company operates brands RateHawk, ZenHotels and RoundTrip in 180+ source markets. Our products help customers select and book all types of accommodation from over 1.7 m options in 220 countries. Our goal is to enable customers to plan all aspects of travel for work and for pleasure. Emerging Travel Group has been founded in 2010, and today employs more than 1 200 people across Europe, CIS, Middle East, and South Africa in roles ranging from product and business development to specialized multilingual customer support for all our customers, whether they are trade partners or individuals simply booking their hotels online. Our mission is to enrich everyone’s travel experience around the world through cutting edge technology and excellent customer service.



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