Data Analytics Engineer

Data Analytics Engineer

About the company

Invia Travel Group is a prominent pan-European online travel agency with over 800 employees. We operate in several European countries, including Germany, Austria, Switzerland, Poland, the Czech Republic, Slovakia, and Hungary.  

We have a variety of online travel platforms that cater to different aspects of travel and accommodation. These platforms include Invia.cz, travelplanet.pl, which offers a wide range of summer and winter tours; Ab-in-den-Urlaub.de, which provides last-minute trips, vacation packages, apartments, flights, rental cars, and a platform that provides flight offers from over 550 airlines; and several others, each specializing in various facets of travel and accommodation. 

Invia Group's story is marked by rapid growth and expansion, having entered seven countries within two years. We merged operations from different countries to form the current Invia Group, a dominant online player in the DACH (Germany, Austria, Switzerland) and CEE (Central and Eastern Europe) regions. 

Invia Group's mission is to help people travel the world. We aspire to become the most customer-centric provider among Online Travel Agencies. We are focused on expanding our position in the online travel market and aim to be a one-stop-shop package platform for customers, offering everything from traditional package tours to tailored individual trips.

About the role

As our first dedicated Analytics Engineer working directly with tech leadership, you will take part in architecting our data-driven transformation - bridging the gap between our existing financial/product analytics foundation and the comprehensive business intelligence we need to compete in today's dynamic OTA landscape.

You're joining at a pivotal moment. Our legacy BI team has built solid foundations around finance and product metrics, creating databases that currently serve core financial and product related reporting needs. However, we're missing critical insights across supply chain operations, customer behavior patterns, anomaly detection, and market dynamics that could unlock significant competitive advantages.

Your responsibilities

Anomaly Detection & Revenue Protection

• Implement automated alerts for pricing anomalies, sudden conversion drops, and inventory gaps that could be costing us lost bookings

• Build real-time monitoring for unusual booking patterns that may indicate technical issues, fraud, or market opportunities

• Create early warning systems for supply chain disruptions (sudden availability drops, price spikes, partner connectivity issues)

Booking Behavior Intelligence

• Deploy machine learning clustering algorithms to segment users by booking journey patterns, identifying distinct behavioral cohorts (price-sensitive browsers, quick bookers, research-heavy travelers)

• Use survival analysis models to predict at what point in the funnel each user type is most likely to convert or abandon, enabling targeted interventions

• Implement sequential pattern mining to discover optimal booking flows and identify deviations that predict abandonment

• Build propensity scoring models that identify high-intent users in real-time for dynamic pricing and personalized experiences

Bounce Rate & User Experience Optimization

• Apply statistical process control to detect when page bounce rates exceed normal variations, automatically flagging UX issues before they impact revenue

• Use multivariate regression analysis to isolate specific UX elements causing abandonment (form field complexity, page load times, mobile responsiveness)

• Implement A/B testing statistical frameworks with proper sample sizing and significance testing to validate UX improvement hypotheses

• Deploy anomaly detection algorithms (isolation forests, z-score analysis) to identify unusual user behavior patterns that indicate technical issues or poor UX design

• Build correlation matrices between user actions (scroll depth, click patterns, time-on-page) and conversion outcomes to pinpoint exact friction points

• Use decision tree models to understand the hierarchy of UX problems - which issues most strongly predict bounce rates across different user segments

Untapped Revenue Opportunities

• Discover underserved routes, dates, and customer segments where we have supply but low visibility/marketing

• Identify cross-sell and upsell opportunities based on booking patterns and customer behavior

• Find pricing arbitrage opportunities where our competitors are consistently over/underpricing

Product Offering Gap Analysis

• Map customer search queries that return zero or poor results, revealing unmet demand

• Analyze competitor booking patterns to identify services/destinations we should add

• Discover customer segments requesting features or services we don't currently offer

• Identify seasonal or regional gaps in our inventory that competitors are capturing

Our requirements

• SQL + Python/R proficiency - Essential for data extraction, transformation, and building ML models. Non-negotiable for daily work.

• End-to-end analytics experience - Must have built complete solutions from data ingestion to business insights/dashboards, managing the full analytics lifecycle independently.

• ML & statistical modeling - Proven experience with clustering, classification, regression, and anomaly detection. Must understand model evaluation, feature engineering, and statistical significance testing.

• Business impact focus - Demonstrated ability to translate business problems into data solutions and communicate insights to non-technical stakeholders. Track record of driving measurable business outcomes.

• Data architecture & warehousing - Experience designing and implementing scalable data pipelines, ETL processes, and data warehouse solutions from multiple source systems.

Nice to have:

• Travel/OTA industry experience - Familiarity with booking funnels, seasonality patterns, supplier relationships, revenue management, and travel-specific metrics saves months of domain learning.

• Advanced ML techniques - Experience with survival analysis, propensity scoring, sequential pattern mining, and real-time recommendation systems for sophisticated use cases.

• Data visualization & self-service BI - Ability to build intuitive dashboards and enable non-technical teams to explore data independently using tools like Looker, PowerBI, MicroStrategy or similar

• A/B testing & experimentation - Knowledge of experimental design, statistical testing frameworks, and causal inference methods for optimizing user experience and business metrics.

Our offer

• Competitive Salary: up to 30 000 PLN net (B2B), commensurate with skills and experience

• Contract: B2B

• Paid Holidays: Enjoy 26 days of paid leave (on B2B)

• Sick Leave: Receive 100% paid sick leave for up to 20 days (on B2B)

• Birthday Leave: Take a paid day off to celebrate your birthday

• Flexible Working Hours: Our core hours are 9 AM to 3 PM

• Hybrid Work Model: Work 2 days in the office and 3 days from home

• Health and Wellness: Shared costs for sports activities and private medical care

• Professional Development: Shared costs for training and courses

• Life Insurance: Comprehensive coverage for peace of mind

• Employee Discounts: Access to corporate products and services at discounted prices

If the above sounds like an interesting opportunity we would be more than happy to hear from you!Please send your resume in English.