Temel
Senior Data Scientist
Yayınlandı: 02.06.2026
Kapanış tarihi: 17.07.2026
İş referansı: cb45e7b7cc6253ae9547197b661af6eb
İş bilgileri
Konum
Geneva, Switzerland
Şirket
TN Switzerland
Müşteri / İşveren
Vorsee
İş referansı
cb45e7b7cc6253ae9547197b661af6eb
Listeleme türü
Temel
AB çalışma izni zorunlu
Hayır
Yayınlandı
02.06.2026
Kapanış tarihi
17.07.2026
İş tanımı
Who we areVorsee (by ZYTLYN Technologies) empowers companies across the $11 trillion travel industry to shape the future with predictive AI solutions that augment commercial planning, sales, marketing, retailing and operations. We work with some of the largest travel brands in the world, and our vision is to answer highly detailed and granular questions about the future of travel, such as demand, supply, market fluctuations and pricing. Our core focus is on airlines, airports, travel agencies, destinations, tourism boards, hotels, car rentals, travel retailers, and luxury brands.Who we are looking forWe are looking for a Senior Data Scientist who is passionate about solving complex data and forecasting problems in the travel industry. You are someone who thrives on turning large-scale, real-world data into accurate, actionable insights and predictions that drive business decisions. You combine strong statistical foundations with practical machine learning expertise and are comfortable owning projects end-to-end from problem framing and data exploration to deployment and monitoring in a cloud environment.You are curious, business-oriented, and collaborative. You understand that forecasting in the travel industry requires both technical excellence and domain awareness, especially when working with seasonality, demand volatility, and external drivers.Location / Contract typeGeneva, Switzerland Office;Full-time, Permanent contract.Our cultureWe have a culture that focuses on empowering people, with team members working in our HQ (Geneva, Switzerland), and all across Europe (e.g. France, Spain, Italy, Poland, UK). We believe a diverse team creates better outcomes and fosters a better environment for learning and growth. We put a lot of emphasis on communication, listening, efficient processes and trusting our team. We rely on each other, and work together to achieve our common goals. We believe in working smart, with strong focus and intensity, tackling every challenge as a team.Your workAs a Senior Data Scientist, you will:Design, develop, and maintain time series forecasting models to predict travel demand, pricing dynamics, and related KPIs.Work with large-scale datasets (e.g., data pipelines, model training).Apply and compare classical statistical models (e.g., ARIMA/SARIMA, ETS, Prophet) and machine learning models (e.g., Random Forest, Gradient Boosting, XGBoost, LightGBM) for forecasting tasks.Explore and implement deep learning approaches where appropriate.Perform thorough data analysis, feature engineering, and validation tailored to time series data (cross-validation strategies, backtesting, handling seasonality and trends).Collaborate with data engineers, product managers, and business stakeholders to translate business needs into scalable data solutions.Ensure high-quality code standards, reproducibility, and documentation.Contribute to model deployment and lifecycle management in production environments.RequirementsBasic requirementsStrong experience (5+ years) in Data Science or Machine Learning roles.Solid expertise in time series forecasting and related evaluation methodologies.Deep understanding of core machine learning algorithms (supervised and unsupervised) and when to apply them.Good familiarity with deep learning concepts and frameworks (e.g., TensorFlow, PyTorch, or similar).Advanced Python skills, including strong knowledge of common data science libraries such as NumPy, Pandas, SciPy, scikit-learn, Matplotlib/Seaborn, and relevant time series libraries.Strong knowledge of statistics, probability theory, and experimental design.Experience with SQL and working with large-scale structured and unstructured datasets.Ability to write clean, maintainable, and production-ready code.Strong communication skills and the ability to explain complex technical concepts to non-technical stakeholders.Resourceful self-starter, comfortable with ambiguity and shifting priorities in a startup;Highly organised, disciplined, and detail-oriented;Bonus pointsExperience in the travel industry or similar demand-driven industries.Knowledge of MLOps practices and tools.Experience with embeddings, vector databases, hybrid search, chunking, reranking, tool-calling, and source-grounded LLM answers. Python/SQL skills and experience building scalable pipelines for large datasets, APIs, databases, indexing, data quality, access control, and production cloud deployment.Experience working in AWS cloud environments (e.g., S3, EC2, Lambda, or similar services).Experience with containerisation and orchestration technologies such as Docker and Kubernetes.Experience building and maintaining CI/CD pipelines for ML workflows.Familiarity with model monitoring, drift detection, and automated retraining strategies.Contributions to open-source projects or published work in forecasting or machine learning.BenefitsWhat we offerJoin a team of exceptional talent — At Vorsee, we hire thoughtfully and selectively, bringing together a small, focused team of high performers. We believe that a lean and empowered team moves faster, builds smarter, and achieves more. You’ll collaborate with driven colleagues who value efficiency, ownership, and impact.Competitive salary- adjusted for experience and market benchmarks.
Yetenekler
apply blended learning
apply for research funding
apply research ethics and scientific integrity principles in research activities
build recommender systems
Business Analytics
Business Intelligence
collect ICT data
communicate with a non-scientific audience
Computational Biology
Computer Simulation
conduct research across disciplines
create data models
Data Engineering
data ethics
Data Mining
Data Models
data quality assessment
Data Science
data visualisation software
define data quality criteria
deliver visual presentation of data
demonstrate disciplinary expertise
design database in the cloud
design database scheme
develop data processing applications
develop professional network with researchers and scientists
Digital Curation
disseminate results to the scientific community
draft scientific or academic papers and technical documentation
empirical analysis
establish data processes
evaluate research activities
execute analytical mathematical calculations
Hadoop
handle data samples
Healthcare Analytics
image recognition
implement data quality processes
increase the impact of science on policy and society
information categorisation
Information Extraction
integrate gender dimension in research
integrate ICT data
interact professionally in research and professional environments
interpret current data
LDAP
LINQ
make data-driven decisions
manage data
manage data collection systems
manage findable accessible interoperable and reusable data
manage ICT data architecture
manage ICT data classification
manage intellectual property rights
manage open publications
manage personal professional development
manage research data
Marketing Analytics
mathematical modelling
MDX
mentor individuals
multidisciplinary research
N1QL
normalise data
online analytical processing
operate open source software
perform data cleansing
perform data mining
perform project management
perform scientific research
promote open innovation in research
promote the participation of citizens in scientific and research activities
promote the transfer of knowledge
publish academic research
quantitative analysis
query languages
report analysis results
Research Design
resource description framework query language
Scientific Computing
scientific literature
Social Network Analysis
SPARQL
speak different languages
State Estimation
statistical modeling techniques
Statistics
synthesise information
teach in academic or vocational contexts
think abstractly
Unstructured Data
use data processing techniques
use databases
use spreadsheets software
visual presentation techniques
write scientific publications
XQuery