Humans & Data: Empowering Skills & Shaping Careers

Workshops + mentorship + panel

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While our main conference in June explores the cutting-edge future of Data Science tools and impact, our Pre-Event in May focuses on the most critical component of the equation: the people.
"Humans + Data" is an interactive, hands-on prequel designed to bridge the gap between technical algorithms and human application. In the age of generative AI and autonomous systems, soft skills, ethical reasoning and career adaptability are becoming just as vital as coding. This event moves beyond lecture-style talks to foster deep connection, skill-building and practical problem-solving in smaller, intimate groups.

What to Expect 

This intensive session is designed to break down barriers between speakers and attendees. Through parallel workshops, an expert panel and extended mentorship, you will gain concrete tools to navigate the ethical and professional challenges of the AI era.

Program Highlights

1. The Panel: Biases in Data/Practice: Sources and Mitigation

 

As AI systems increasingly influence hiring, evaluation and decision-making processes, data science is no longer only a technical discipline, it is a social one. Responsible data science requires not only accurate models, but also awareness of how data, algorithms and organisational practices shape real outcomes for people.

One of the areas where these challenges become most visible is the job market. Bias embedded in datasets, models or deployment decisions can subtly influence how candidates are evaluated, how career paths evolve and how opportunities are distributed, often reinforcing existing inequalities.

In this panel, our speakers will explore how biases emerge across the data science lifecycle  from data collection and annotation to model design and deployment, and what organisations can do to detect and mitigate them. We will also discuss how professionals, and especially women, can navigate these dynamics, stay relevant and grow their impact as AI reshapes roles, expectations and decision-making structures.

The goal is not only to identify problems, but to share practical lessons on how responsible and ethical data science can be implemented in real organisational environments.

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2. Interactive Workshops (Parallel Tracks)

 

The event will include 5 workshops. Workshops will run in parallel and are intentionally designed to be hands-on and interactive, encouraging active participation rather than lecture-style presentations.

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The goal is to give participants concrete tools they can apply in their work and careers, while also creating opportunities for direct exchange with experienced practitioners.

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The workshops will cover two main areas:

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1. Technical workshops (3 sessions)

Focused on practical aspects of working with data science and AI systems. These sessions will explore real-world use cases, methodologies and tools used in modern data workflows. Detailed descriptions of these sessions will follow as the speakers finalise their topics.

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Workshop 1: Architecting Independence: Building Your Own Private Model-as-a-Service (MaaS) (Camille Nigon, Red Hat)

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That third-party LLM API bill just landed. It’s… impressive. And so are the questions from your security team about where your proprietary data is actually going. While the world sprints to integrate AI, many of us have become "API-dependent," trading control for speed and creating massive risks in the process. It’s time to break free from the proprietary black box and take back your AI destiny.

This session is for engineers and data scientists who want to move beyond just calling an API. We’ll roll up our sleeves to architect a private MaaS platform using powerful open-source models. This is a practical blueprint for leveraging the open-source ecosystem to tackle the real-world challenges of data sovereignty, observability, and infrastructure control.

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In this session, you will deploy an open-source model to a secure private endpoint, integrate it into your own AI-powered code assistant, and track real-time usage and costs through Grafana dashboards.

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Leave this session with a concrete playbook to stop being a consumer and start being a provider. Gain the technical confidence to deploy open-source LLMs, manage infrastructure at scale, and lead the conversation on transparent, secure AI strategy.

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Workshop 2: Applied ML and GenAI at AXA Switzerland (Nadine Golinelli, Timo Stöttner AXA Switzerland)

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Moving from traditional predictive machine learning to Generative AI redefines the challenge of model evaluation. When a model generates complex text and reasoning rather than a simple classification, standard metrics like accuracy, precision, etc., fail. One of the greatest difficulties in developing GenAI applications that reliably perform in real-world insurance use cases is how to reliably determine whether the output is correct. 

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Workshop 3: Unlocking Potential: How We Develop Talent & Leverage AI (Nathalie Spielmann, Christin Husteden, Deloitte)

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The workshop will cover two key areas:

• Learning & Development — Our practitioner learning journeys and how we support career growth

• Innovation & AI — How we leverage AI internally and the tools we use to enhance delivery

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2. Professional & communication workshops (2 sessions)

Focused on essential soft skills that help professionals navigate the evolving AI and data landscape, including communication, leadership presence and professional positioning.

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Workshop 1: Present Yourself - Elevate Your Leadership Presence (Tara Brodin)

Participants will learn how to connect with an audience in a genuine and impactful way. Through focused voice work, we’ll develop key communication skills that enhance clarity, presence, and engagement. Additionally, we’ll explore the power of nonverbal communication, equipping your team with practical tools to present themselves with confidence and authenticity.

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Workshop 2: Building Your Personal Brand with AI (Tata Matesyan)

As AI tools increasingly influence how professionals communicate and share their work, developing a clear and authentic professional presence is becoming more important than ever.

This workshop explores how AI can support professionals in positioning their expertise, communicating their ideas effectively and building visibility in the data and AI ecosystem.

Through practical examples and interactive exercises, participants will explore ways to use AI tools responsibly while maintaining authenticity and credibility in their professional communication.

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3. Extended Mentorship & Networking 

 

1. Upskilling & Networking in Switzerland (Priska Burkard)

   • Where to find learning opportunities

   • Communities and networks worth joining

   • Strategies for networking in Switzerland

   • Building meaningful professional relationships

2. Ethics by Design – Integrating Digital Ethics into Practice (Christina Meyer)

   • Practical tools and frameworks for ethical AI

   • Integrating ethics into data and product workflows

   • Building AI literacy witanohin organisations

   • Lessons from implementing responsible AI

3. Navigating the Swiss Job Market (Magalie Heraud)

   • Portfolio careers in Switzerland

   • Finding jobs in the Swiss data and AI ecosystem

   • How hiring works in Switzerland

   • What employers value most

4. Career Development in AI & Data (Natalya Tarasova)

   • Career transition

   • Leadership paths in technical roles

   • Overcoming career plateaus

   • Balancing technical depth with strategic influence

5. Agentic AI and Ethics (Ursula Maria Meyer) 

   • The technical side of Agentic AI

   • New skills that are needed in relation to Agentic AI and Ethics

6. Data Science beyond the Model (Yee Ling Gröschel)

   • Identifying problems worth solving 

   • Turning complex real world problems into solvable data problems

   • From analysis to real world impact

   • Ethical responsibility when working with human and organisational data

7. Building Your Intelligence Advantage (Dr. Jess Conser)

   • Identifying uniquely human skills and perspectives

   • Creating value through human judgment

   • Using AI to amplify thinking and productivity

   • Exploring where human–AI collaboration creates value

8. Career alpha in the age of AI (Chenxin Nie) and Working with AI as a Quant Researcher (Ming Ding)

   •  Usage of AI to improve quant work and what still remains human

   • Working with financial data, particularly its noisy nature and high uncertainty how these characteristics shape the way of using AI tools, as well as the continued importance of human’s role in decision-making
      

Why Attend?

Connect Early: Build your network before the massive June conference.
Get Hands-On: Move from listening to doing with interactive workshops.
Interact: Smaller group sizes ensure you can ask questions and engage directly with experts.