Lightly AG is an ETH and HSG spin-off pioneering in machine learning and computer vision. Backed by Y Combinator and top-tier investors, our technology is used by global leaders in autonomous driving, medical imaging, and visual inspection.

With a small but sharp team in Zurich, we’re looking for analytical and driven Data & ML Experts to help us translate data-related tasks into AI-readable formats.

This role suits someone with a background in mathematics, data science, computer science, or data engineering with experience in any of the following:

• Product Data Science / Experimentation
• Machine Learning Engineering (simple models, feature engineering)
• Data / Business Intelligence Analysis
• Data Engineering / Pipeline Development

The minimum expected time commitment for this position is 10 hours/week.

You’ll be a good fit if you have 2-3 years of experience working at top firms in data or ML fields and experience in at least some of the following tools:

• Command-line / Terminal use
• SQL for querying structured data
• Python (with Pandas, Scikit-learn, Matplotlib)
• Jupyter Notebooks / Colab
• Tableau, Looker, or Power BI for visualization
• Spark, Hadoop, Kafka for big data processing
• Cloud Data Warehouses (BigQuery, Snowflake, Redshift)

Specific tasks may include :

• Analyzing and visualizing data to generate business insights
• Designing and interpreting experiments (A/B tests)
• Building, evaluating, and improving simple ML models
• Developing and maintaining data pipelines and ETL processes
• Creating dashboards and reports to track key metrics

You’re a strong candidate if you:

• Are fluent in English
• Have strong analytical and quantitative skills and are confident working with data
• Communicate clearly and precisely
• Are based in Zurich

• A front-row seat to how a YC-backed deep tech company is built
• Direct exposure to the inner workings of startup leadership
• Flexible working hours and the ability to shape your role over time
• Competitive compensation tailored to experience and scope of work

Send us your CV and a short note about why this role excites you. If you’ve handled similar tasks before, we’d love to hear specific examples.

We look forward to hearing from you!