Lead Data Science; f|m|d Hybrid model

Company Overview

Welcome to SMG Swiss Marketplace Group!

SMG is a pioneering network of online marketplaces and a leading European digital company that simplifies people’s lives with forward-looking products. We operate leading marketplaces across real estate, automotive, general classifieds, and finance & insurance. We’re driven by our values:
Better Together, Aim High, and Act Responsibly.

Meet the team! At SMG, our strength lies in our people. Meet some of the team members with whom you could work:

• Janine Lee - Director Data - Linked In
• Dmytro Yurchenko - Senior Machine Learning Engineer - Linked In
• Vukasin Vasiljevic - Machine Learning Engineer - Linked In
• Marcel Schumacher - Data Product Manager - Linked In

As a at Swiss Marketplace Group s Real Estate Business Unit, you will contribute to the data hub for the leading real estate platforms in Switzerland, which includes homegate.ch and immoscout
24.ch, among others. You will be part of a cross-functional, agile data team with an open mindset and teammates who enjoy learning new skills and sharing theirs.

The Lead Data Scientist will be responsible for developing and implementing data science solutions that drive business growth and innovation. The ideal candidate will have a strong background in building data science, machine learning, and generative AI use cases. The Lead Data Scientist is a senior-level position strongly focused on technical leadership (100% hands-on) and opens a path to a technical career track.

• You will design and implement data science and machine learning use cases to bring value to our users and solve business challenges
• You will be the tech lead for data-science projects and teams to align with business needs and deliver value
• You will provide technical guidance, suggest best practices, and drive team agreements related to best practices
• You will perform exploratory data analysis on large and complex datasets to identify patterns, trends, and relationships, and ultimately generate high-quality data and relevant hypotheses
• You will lead implementations of Generative AI use cases, from conceptualization & experimentation to implementation and monitoring
• You will develop and apply ML/AI techniques and best practices for reliable, scalable, and ethical data-driven solutions
• You collaborate with stakeholders to understand the specific objectives and goals of projects, and aid in designing a formal way of evaluating the systems’ performance against these
• You will write, review, and debug code for complex projects and lead solution development and alignment
• You will own and further develop our in-house models in many different areas, such as inventory classification, predictions, recommendations or fraud detection
• You will report directly to the Head of Data Engineering & Science

• 5+ years of experience in building data science projects
• Deep understanding of data science pipelines, including data ingestion, feature engineering, model training, deployment, and monitoring
• Experience with data lineage, data transformation, data modelling, data storage, data access, and data quality assessment techniques is essential for effective model development and productionalization
• Experience working with a high volume of heterogeneous data
• Strong programming in Python (and preferably also SQL) and data modelling skills
• Experience with bringing models to a production environment (deployment, retraining, experiment tracking)
• Successful track records of product ionizing machine learning models
• Capable of investigating, familiarising, and mastering new data sets quickly
• Ability to work well/synergise with different teams and to deal with ambiguity
• Attention to detail in complex environments
• Strong dedication to driving change with a positive can-do attitude
• A proactive approach to learning and finding solutions outside the direct area of competence
• Fluency in English, both written and verbal
• Eager to keep up to date and leverage the latest ML technologies in a broad and challenging business environment

• 6 weeks of holidays per year (plus option to buy 10 extra)
• 40-hour work week with flexitime (capped at 45 hours)
• A hybrid…