Data Scientist

Company Description

Founded and headquartered in Switzerland, Avaloq is continuously expanding its global footprint with around 2,500 colleagues in 10 countries, and more than 160 clients in 35 countries. We are an industry-leading provider of wealth management technology and services for financial institutions around the world, including private banks and wealth managers, investment managers, as well as retail and neo banks. Our research led approach and continual innovation is powered by the passion and creativity of our colleagues.

We are always looking for talented people to join us on our mission to orchestrate the financial ecosystem and democratize access to wealth management. Avaloq offers the opportunity to work closely with some of the world’s leading financial institutions as we jointly develop and shape careers. Championing a collaborative, supportive and flexible work environment empowers our colleagues to reach their full potential.

**Job Description**:
**Your team**

In our Domain, we are responsible for collecting large amount of data, their analysis and interpretation, creating dashboard and cockpit development, procedure and modeling using machine learnings. We are responsible for quality and reliability of data using latest tools and technologies

**Your mission**:

- Design, implement and manage ML based solutions using state of the art models and deploy them using Kubernetes and DevOps best practices
- Produce high quality, maintainable and efficient code and write documentation of implementation
- Portal & dashboard creation using low code platform
- Correlate event & app logs & trace and analyze them using ML & AI
- Prevent incidence by proactive solutioning
- Ensure code adheres to security standards

**Qualifications**:
**Which skills should you bring to the pitch**:

- ** University Degree. **in a scientific discipline such as mathematics, data science, IT or physics. Ideally, you also hold a master’s degree or PHD.
- ** Proficiency. **Minimum 3+ years of experience as Data Scientist.
- ** Programming Skills. **Strong programming skills in Python, R, or similar languages and gained experience in Machine Learning.
- ** Tools.** Proficient with dashboarding tools such as Tableau, Power BI QlikSense, Domo, or similar enterprise tools.
- ** Technical background.** Solid technical background with a complete understanding of database design and modelling using Redshift, MySQL, SQL Server, or other relational databases.
- ** Analytical Thinker. **Passion for analytics and strong analytical abilities.
- ** Teamwork.** Experience in working closely with a data team or an analytics team.

**Who we’re looking for**:

- ** Agile Mindset. **This is about learning and adapting, continuously improving what we do to deliver a valuable product to our customers. You collaborate and communicate leading to team success.
- ** Team player**. We love learning from each other, great ideas are shaped and inspired by other ideas in order to achieve the simplest, smartest and safest solution.
- ** Innovative.** We create space for ideas and love to use the newest technologies. To be cutting edge, we need to stay on top and deliver an amazing digital experience.

**What you need**:

- Master's or PhD in statistics, mathematics, computer science, or a related field
- 3+ years of experience as a Data Scientist or similar role
- Experience with big data technologies
- Strong problem-solving and critical thinking skills
- Excellent communication and collaboration skills
- Natural Language Processing (NLP)

**Key Notes**:

- Data scientists need to have a solid understanding of statistics and mathematics to be able to design and implement statistical models, interpret data, and draw meaningful insights from it.
- Machine learning is a key area of expertise for data scientists. They should be proficient in machine learning algorithms, such as decision trees, random forests, and neural networks, and know how to use them to solve real-world problems.
- Data Visualization: Data scientists should be able to create effective data visualizations that communicate complex information in a simple and clear way. They should have experience with tools such as Tableau, PowerBI, or others.
- Cloud Computing: Data scientists should have experience with cloud computing platforms such as AWS, Azure, or Google Cloud, or Oracle Cloud. They should know how to deploy machine learning models and manage data in the cloud.
- Should have a strong technical background and be able to work with large, complex data sets to extract meaningful insights and drive business decisions.
- Experience with containerization and container orchestration tools such as Docker and Kubernetes

Added advantage for
- Git, Gradle and Jenkins CICD toolchains. GitOps experience is a plus
- Deep learning and predictive analytics
- Backend development skills in Java

Additional Information

We realize that managing work life balance is a challenge we all f