Senior Data Scientist

Jobgether SRL; Schweiz; Remote; CHF 127.000 - 171.000; Vollzeit

Benefits dieser Stelle

Fully remote

Global team

Competitive compensation

Zusammenfassung

Jobgether SRL is seeking a Senior Data Scientist based in Switzerland for a fully remote role focused on high‑volume real-time identification platforms. You will work with noisy, unlabeled data to create advanced ML approaches, spanning research to production deployment and real-time service integration.

You’ll lead end‑to‑end DS initiatives, shape engineering practices, and collaborate across teams in a distributed international environment.

Qualifikationen

• 5+ years in machine learning, data science and backend engineering.
• Strong fundamentals in ML and statistics.
• Experience with supervised, semi-supervised and unsupervised learning.
• Proven real-time ML services development and model-to-service integration.
• Excellent coding and software engineering skills, including SQL and CI/CD.

Aufgaben

• Develop data-driven algorithms on noisy unlabeled data to improve browser and device identification.
• Design experiments for real-time inference and model-service integration.
• Own DS initiatives end-to-end from research to production deployment.
• Collaborate with data science and engineering to productionize ML concepts.
• Participate in a shared on-call rotation with advance scheduling.

Kenntnisse

Machine learning

Backend development

SQL

Go

Python

Git CI/CD

Communication

English fluent

Ausbildung

Advanced degree in a relevant field

Tools

ClickHouse

Snowflake

BigQuery

dbt

Superset/Looker/Tableau

Pinecone/FAISS/Qdrant

AWS

Jobbeschreibung

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Scientist based in Switzerland.

This is a senior, hands-on data science role focused on improving the accuracy and intelligence of a high-volume, real-time identification platform. You’ll work with complex, noisy, and often unlabeled data to develop machine learning approaches that distinguish browsers and devices with greater precision. The role combines advanced machine learning, statistical analysis, experimentation, and backend engineering in a highly technical environment.

You’ll own projects from initial research and experimentation through production deployment and integration with real-time services. You’ll also help shape engineering practices, data-driven decision-making, and effective approaches to machine learning across the wider team. This is a fully remote opportunity suited to someone who enjoys solving challenging problems where research, software engineering, and applied ML meet.

Accountabilities

• Develop data-driven algorithms using raw, noisy, and unlabeled data to improve browser and device identification capabilities.
• Design and implement supervised, semi-supervised, and unsupervised machine learning approaches, including methods for high-cardinality categorical data.
• Own data science initiatives end to end, from problem definition and experimentation through production deployment and integration with real-time services.
• Design experiments and technical solutions for real-time inference, model-to-service integration, training automation, and other machine learning engineering challenges.
• Conduct exploratory data analysis to investigate business and technical questions, identify anomalies, and evaluate model and dataset performance.
• Develop practical approaches for collecting and evaluating data when labeled datasets are limited or unavailable.
• Contribute to an engineering-focused, data-driven culture by sharing tools, methodologies, and effective data science practices with colleagues.
• Collaborate across data science and engineering functions to turn machine learning concepts into reliable, production-ready services.
• Participate in a shared on-call rotation, with schedules communicated in advance and coverage designed to minimize disruption outside normal working hours.

Requirements

• 5+ years of professional experience spanning machine learning, data science, and backend development or closely related engineering disciplines.
• Advanced knowledge of machine learning fundamentals and statistical methodologies.
• Strong practical experience with supervised learning, including gradient boosting and approaches for high-cardinality categorical data.
• Hands-on experience with semi-supervised and unsupervised learning techniques.
• Strong exploratory data analysis and creative problem-solving skills, particularly when working with incomplete, noisy, or unlabeled datasets.
• Proven experience developing real-time machine learning services, including model inference and integration between models and production applications.
• Ability to transform machine learning models into minimum viable real-time web services and production-ready solutions.
• Excellent coding and software engineering skills, including strong SQL capabilities and familiarity with Git, CI/CD pipelines, IDEs, and shell scripting.
• Strong communication skills and fluent English, with the ability to collaborate effectively in a distributed international environment.
• A research mindset and academic background are advantageous.
• Experience with Go and backend development is a plus.
• Familiarity with analytical data platforms such as ClickHouse, Snowflake, or BigQuery is beneficial.
• Experience with data transformation frameworks such as dbt, visualization tools such as Superset, Tableau, or Looker, or vector databases such as Pinecone, FAISS, or Qdrant is a plus.
• Experience building embedding-based search systems is advantageous.
• Familiarity with technologies such as Go, SQL, advanced ML frameworks, ClickHouse, dbt, and AWS is beneficial.

Benefits

• Competitive compensation, with the source role indicating a US cash compensation range of $152,000-$205,000 USD; compensation ranges are location-specific and may differ for candidates based in India.
• Fully remote working environment.
• Opportunity to work on challenging machine learning problems involving real-time systems, large-scale data, and advanced device intelligence.
• Exposure to modern machine learning, data engineering, backend development, and cloud infrastructure technologies.
• Opportunity to contribute to technical strategy and influence engineering and data science practices.
• Collaboration with a globally distributed team.
• Inclusive environment that values diverse experiences, perspectives, and backgrounds.
• Candidates must be authorized to work from their home location; visa sponsorship is not provided.
• Participation in a shared on-call rotation with advance scheduling and an effort to balance coverage fairly while minimizing off-hours disruption.

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