Data Scientist GenAI Customer Service (m/f/d)

As a Data Scientist GenAI Customer Service at SIXT, your main responsibility will be to engage with multiple stakeholders to transform business challenges into technical solutions. You'll work closely with software development engineers and data scientists to design Generative AI-driven solutions. This involves enhancing software development processes and empowering engineers to utilize Generative AI effectively.

To qualify for the Data Scientist GenAI Customer Service position at SIXT, you should have substantial hands-on experience with engineering and Generative AI. A solid knowledge of Python and AWS, as well as experience with Open AI, AWS Bedrock, and orchestration frameworks like LangChain, are essential. Familiarity with LLMOps and CI/CD approaches will also be critical.

SIXT invests in the professional growth of employees, offering access to training programs, external conferences, and internal tech talks. As a Data Scientist GenAI Customer Service at SIXT, you'll have ample opportunities to enhance your skills and stay updated with the latest advancements in Generative AI and data science.

The work environment at SIXT is designed to promote a healthy work-life balance with flexibility. You will benefit from a hybrid working model, flexible hours, and a relaxed dress code, all aimed at fostering a positive and productive atmosphere for Data Scientists like yourself.

As a Data Scientist GenAI Customer Service at SIXT, you can enjoy generous time off, including 28 vacation days, additional time off for your birthday, and a volunteer day each year. Along with health insurance and various employee discounts, SIXT is dedicated to promoting the well-being and satisfaction of its workforce.

When answering this question, provide specific examples of Generative AI projects you've been involved in, the tools you used, and the impact on the business. Highlight your familiarity with technologies such as Open AI and AWS Bedrock, emphasizing your understanding of their relevance in real-world applications.

Start by discussing your process of engaging with stakeholders to understand the core business challenges. Explain how you gather requirements, brainstorm potential solutions, and iterate on feedback received from both technical and non-technical team members.

Focus on your proficiency in Python and any other relevant languages like Java or Go. Provide concrete examples of applications you've developed or contributions you've made in previous roles that leveraged your programming skills, particularly in relation to Generative AI.

Highlight your communication style and collaborative approach. Discuss how you ensure a seamless workflow by understanding their perspectives and needs, and how you adapt your technical solutions to accommodate typical software development hurdles.

Demonstrate your knowledge of the LLMOps paradigm, outlining its importance in managing machine learning lifecycle effectively. Provide specific examples of projects where you utilized LLMOps practices to improve deployment and performance of Generative AI solutions.

Share your strategies for staying informed, such as following industry blogs, attending conferences or webinars, engaging in online courses, or participating in tech talks. This demonstrates your commitment to continuous learning, which is valuable for this role.

Identify specific challenges you've encountered, whether technical or logistical, and explain the steps you took to address them. Highlight your problem-solving abilities and impact through a positive outcome in your projects.

Elaborate on your belief in team knowledge sharing, and describe methods you've employed to promote it—like hosting workshops, creating documentation, or utilizing collaborative platforms for sharing insights and learnings from projects.

Discuss your understanding of CI/CD processes and any tools or practices you've implemented in past roles. Explain how you would integrate CI/CD approaches into Generative AI projects to enhance efficiency and ensure production-grade solutions.

Share your personal passion for data science and Generative AI. Discuss what excites you about these fields, whether it's the potential to create innovative solutions or the ability to improve customer experiences, and how this aligns with your career goals.