Beschreibung & Anforderungen
The Infor Revenue Management System (RMS) team is seekin a talented Senior Data Scientist with a specialization in Machine Learning (especially GenAI & LLMs). Infor RMS is one of the market leading solutions developed for the hospitality industry and installed within the biggest hotel groups in the world.
Infor RMS is a revenue management cloud-based solution that automatically, on a daily basis, calculates demand and revenue forecasts, while recommending appropriate selling strategies. Those recommendations are then uploaded to hotels’ websites or to online travel agencies (Booking.com, Expedia…).
As a senior data scientist, you are expected to have expertise in natural language processing (NLP). The ideal candidate will possess a strong background in statistics, machine learning, and data analysis, with a proven track record of finetuning, prompting and deploying state of the art LLMs. The role requires a deep understanding of LLMs and how to use them to extract insights from data.
Your Responsibilities Include
- Prompt Engineering: Use your knowledge in prompt engineering techniques to write efficient and accurate prompts to extract insights out of structured and unstructured data.
- LLM Finetuning & Integration: Train state of the art LLMs on synthetic data and ensure they integrate seamlessly into our business processes.
- Data Analysis and Interpretation: Conduct in-depth analysis of historical data and trends to identify patterns, correlations, and anomalies that can inform future business strategies.
- Documentation and Communication: Program and write maintainable and well-documented code and write summaries and reports to present technical findings/conclusions and project status updates.
Knowledge and Skills, You Bring to the Organization
- Intelligent, fast-thinking and highly motivated with a strong problem-solving and analytical skills.
- Proven experience in a data science role with a focus on NLP (especially LLMs) and insights generation out of structured and unstructured data.
- Experience with prompt engineering techniques, LLM finetuning and familiarity with LLM-based workflows/architectures such as retrieval-augmented generation.
- Experience with Python (NumPy, Pandas, etc) must have experience in at least one of the common LLM toolkits, such as Langchain, LLamaIndex, etc…
- SQL for databases querying.
- Clear knowledge of a variety of machine learning techniques (especially for time series forecasting) and of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests, etc.) is a huge plus.
- Excellent presentation, written, and verbal communication skills for coordinating across teams.
- Good balance between Data Science and Software Development.
- Be able to work independently and as part of a team.