Senior Data Scientist
Role details
Job location
Tech stack
Job description
- 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.
Requirements
Do you have experience in SQL?, Do you have a Master's degree?, We 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., Basic requirements
- Strong 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 points
- Experience 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.
Benefits & conditions
What we offer
- Join 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.