Senior Data Scientist

About Us

TravelPerk is a hyper-growth SaaS business travel platform and a pioneer in the future of travel for work. Its all-in-one platform gives travelers the freedom they want whilst providing companies with the control they need. The result saves time, money, and hassle for everyone.

TravelPerk has industry-leading travel inventory alongside powerful management features, 24/7 customer support, state-of-the-art technology, and consumer-grade design.

Founded in 2015 and headquartered in Barcelona, we’ve grown to over 1,400 people across Europe and North America. In 2022 we became a ‘unicorn’ and in 2025 we raised $200 million in a Series E funding round, increasing our valuation of $2.7 billion.

We’ve been winning awards too. Since 2023, we’ve been voted one of the best places to work, one of the fastest-growing apps and tech companies, and a leading pioneer of business travel.

These are just some of the reasons why global brands like Wise, Red Bull, GetYourGuide, and Aesop trust us to get the most out of their travel

As a (Senior) Data Scientist specializing in forecasting for Customer Care, you will be responsible for developing predictive models to estimate future contact volumes, staffing needs, and operational trends. You will analyze historical data, identify patterns, and apply statistical and machine learning techniques to improve forecast accuracy, ensuring efficient resource allocation and capacity planning. Collaborating with Workforce Management, Operations, and Product teams, you will help drive data-driven decisions that enhance service efficiency and customer experience.

Responsibilities

• Develop and Maintain Forecasting Models – Build and refine predictive models to estimate contact volumes, staffing requirements, and customer service demand using statistical and machine learning techniques.
• Analyze Historical Trends – Identify patterns in customer inquiries, seasonality effects, and external factors (e.g., disruptions, product changes) that impact customer care demand.
• Optimize Staffing and Resource Allocation – Work closely with Workforce Management to align forecasting outputs with staffing strategies, ensuring optimal agent availability.
• Evaluate Forecast Accuracy – Continuously assess model performance, implement improvements, and incorporate feedback to enhance prediction reliability.
• Conduct A/B Testing and Scenario Analysis – Simulate different business conditions and operational changes to measure potential impact on workload and service levels.
• Collaborate with Cross-Functional Teams – Partner with Operations, Finance, and Data to integrate forecasting models into decision-making processes and automation efforts.
• Monitor and Report Key Metrics – Develop dashboards and reporting tools to track forecast performance and provide actionable insights to leadership.
• Stay Up-to-Date with Industry Best Practices – Research and implement the latest forecasting techniques and technologies to enhance customer care efficiency.

Competencies & Requirements

• 3+ years of experience – as a Data Scientist or similar role

Great communication skills – You can explain technical findings in a way that non-data folks understand, both written and spoken, in English.

• A knack for numbers – You should be comfortable with time series forecasting, regression models, and machine learning techniques to predict customer service demand.

You will need to prove the following

• Coding skills – Strong experience with Python or R as well as SQL to build and refine forecasting models.
• Forecasting know-how – Hands-on experience with tools like Prophet, ARIMA, XGBoost, or similar forecasting methods.
• Data wrangling & visualization – You can clean, process, and analyze large datasets, and turn them into clear insights using Pandas, NumPy, or Looker.
• Customer service operations understanding – You know how things like workforce planning, service levels, and ticket volumes impact forecasting.
• Proactive & self-driven – You take ownership of projects and continuously improve models and processes.

How we work
Our Vision is for a world where TravelPerk is the platform for human connection in real life (IRL). We take an IRL-first approach to work, where our team works together in person 3 days a week. For roles in Customer Care, this can be up to 5 days per week in the office. As such, this role requires you to be within commuting distance of our hubs. We fundamentally believe in meeting in real life to improve connectivity, productivity, and creativity, ultimately making us a great workplace.

At TravelPerk, we prioritize experience and potential over academic qualifications for this role. We believe that talent and ability aren't always reflected in formal credentials.

TravelPerk is a global company with a diverse customer base—and we want to ensure that the people behind our product reflect that. We're an equal opportunity employer, meaning you're welcome at TravelPerk regardless of your appearance, where you're from, or anything else that makes you.

All official communication from TravelPerk comes from @travelperk.com email addresses, our verified social media channels, or recruiters listed on our official LinkedIn page. We will never ask candidates to pay for equipment or make any kind of payment during the hiring process. If you receive an unexpected message claiming to be from TravelPerk and asking you to take action, please forward it to security@travelperk.com and we’ll confirm whether it’s legitimate.