Building the bank of tomorrow takes more than skills.
It means combining our differences to imagine, discuss, code, develop, test, learn… and celebrate every step together. Share our vibes? Join Swissquote to unleash your potential.
We are the Swiss Leader in Online Banking and we provide trading, investing and banking services to +500’000 clients, through our performant and secured digital platforms.
Our +1000 employees work in a flexible way, without dress code and in multicultural teams.
By having a huge impact on the industry, they are growing their skills portfolio and boosting their career in a fast-pace environment
We are all in at Swissquote. As an equal opportunity employer, we welcome candidates from all backgrounds, experiences and perspectives to join our team and contribute to our shared success.
Are you all in? Don’t be shy, apply!
Job Description
Swissquote is looking for a Junior Data Scientist to join our rapidly expanding Quantitative Research & Solutions department. This is an exciting opportunity for recent graduates with relevant internship experience in data science, machine learning or related fields, who are eager to launch their career in a fast-paced and innovative environment.
Responsibilities
- Develop machine learning models.
- Design and develop data pipelines.
- Perform statistical data analysis.
- Develop and experiment with generative AI models, including leveraging proprietary APIs and fine-tuning pre-trained models for custom applications.
- Rapidly prototype models and conduct experiments to validate hypotheses and improve model performance.
- Work closely with cross-functional teams to gather requirements and deliver data-driven solutions.
- Communicate complex findings and insights to both technical and non-technical stakeholders, supporting data-driven decision-making.
Qualifications
- Educational Background: Master’s degree in Data Science, Physics, Mathematics, Computer science or a related quantitative field.
- Experience: One or more relevant internships in data science, machine learning, or AI-related fields.
Technical Skills:
- Solid programming skills in Python, including experience with data manipulation and analysis libraries (e.g., pandas, NumPy).
- Hands-on experience developing machine learning models, either in academic projects or through internships, using libraries such as Scikit-learn, TensorFlow, or PyTorch.
- Familiar with version control tools
- Good understanding of statistical analysis techniques, including hypothesis testing, anomaly detection, and data modeling.
- Proficient in creating data visualizations using tools such as matplotlib, seaborn, or dashboards to communicate insights effectively.
- Basic understanding of LLM architectures (e.g., Transformer-based models) and experience experimenting with LLM APIs (such as OpenAI or Hugging Face) is a strong plus.
Soft Skills:
- Eagerness to learn and grow in a fast-paced environment.
- Good communication skills and team spirit.
- Analytical and problem-solving mindset.
- Ability to take initiative and manage time effectively.
