(Internship) Ai

vor 2 Wochen

Lausanne, Schweiz ELCA Vollzeit

Job number- 1224- Date posted- Feb 15, 2023- Job category- BI / Big Data- Level of experience- Job type- External- Employment type- Internship- Work site- Lausanne- Company JOB BENEFITS

Pleasant work environment

Learning and development

Employee benefits

Attractive compensation

Career guidance
- Your role

Detecting trends in technology usage and skill demand is critical to fulfill a company’s requirements for talent growth. In this context, Artificial Intelligence has the potential to improve talent and workforce management strategies by providing advanced analytics on the profiles and competences currently present within the enterprise.

Studying and modeling the composition and evolution of the workforce in terms of skills, competences and compatibility to specific workloads and projects is a necessary first step towards AI-supported solutions for talent management.

Based on this complex data product, you will investigate retrieval and prediction tasks, as well as visualizations that provide valuable analytical insights. Finally, you will explore the industrialization of your approach.

**What you will learn**:
You will be a Junior Data Scientist for the ELCA Data Science team, developing your skills in the Machine Learning domain under the guidance of experienced data scientists. You will tackle a concrete problem, with real-world enterprise data, helping ELCA in modeling and taking advantage of its knowledge bases.

**Challenges**:
To be successful, you will be in regular contact with your supervisors and find out about the needs and pain points in the company. You will perform data analyses, develop, and evaluate solution prototypes and communicate your results.

**Objectives**:

- Define and harmonize the collection of data from internal sources (CV database, AD & Organigram, Project database, CRM).
- Propose a data modeling approach for the construction of a comprehensive enterprise talent map (graph), complete with all the entities and relationships of interest.
- Evaluate the structure and performance of the talent map on information retrieval and inference tasks: predict the best skillsets/hires to complement a team, determine the best profile matches to projects, retrieve the most relevant resources according to queries.
- Explore visualization approaches based on the current and past structure of the talent map (evolution of skills over time, relationship between skills and career trajectory, clustering of competences according to the organizational structure).

Evaluate and mitigate problems related to principles of responsible AI usage, such hidden biases and removal of personal identifiable data.
- Our offer
- A dynamic work and collaborative environment with a highly motivated multi-cultural and multiples international sites team
- Personal development through training and coaching
- A flat hierarchy and a culture of collaboration across all disciplines
- The chance to make a difference in peoples’ life by building innovative solutions
- High innovation and research backed up by collaboration with universities like EPFL
- Various internal coding events (Hackathon, Brownbags), see our technical blog
- Monthly After-Works organized per locations
- Good life balance (41 working hours per week and possibility to work 2 days per week from home)
- Your profile

**Knowledge**
- Data modeling and engineering
- Data analysis and visualization
- Machine Learning & Natural Language Processing
- Knowledge Graphs and Graph ML is a plus

**Skills**
- Solid Python skills, good software engineering practices
- ML/DL frameworks, Data Viz libraries

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