9 meilleures offres (python developer, switzerland) (à pourvoir)

Data Scientist, Marketing Analytics
SonarSource —Genève, GE
- 100%
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il y a 1 jour
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Postuler rapidement
il y a 1 jour
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CERN —Genève, GE
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- Anglais
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il y a 1 jour
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Google —Zürich, ZH
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- Niveau Master
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Lonza —Bâle, BS
- 100%
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- Anglais
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- Aide au déménagement
il y a 3 jours
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SonarSource —Genève, GE
- 100%
- Java
- Niveau Master
- AWS
il y a 10 jours
Robot Client SDK Engineer (Mensch)
Neura Robotics —Zürich, ZH
- 100%
- Java
- C++
- Python
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SW & FW Developer / Physicist (EP-ATL-TRG-2026-123-GRAP)
CERN —Genève, GE
These algorithms will be implemented on state-of-the-art field programmable gate array (FPGA) systems, which employ novel system-on-chip architectures capable…
De 6 372 CHF à 7 004 CHF par mois
Postuler rapidement
il y a 1 jour

Je souhaite recevoir la dernière alerte Emploi pour les postes de ce type : python developer (switzerland)

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Data Scientist, Marketing Analytics

SonarSource -
Genève, GE

Soumettre votre candidature

Détails de l'emploi

100% | Temps de travail : 90-100%
Il y a 1 jour

Avantages

Logement

Qualifications

SQL
Esprit d'analyse
GitHub
Technologies de l'information
Compétences en communication
Python
Marketing

Description complète du poste

Who is Sonar?

Sonar is driving the future of agent-centric software development. As the leader in AI code verification and governance, we solve a critical problem: ensuring that software generated by AI-assisted developers or autonomous agents is reliable, secure, and maintainable.

Integrating seamlessly with Claude Code, Codex, Cursor, GitHub Copilot, Gemini, and Devin, we help over 75% of the Fortune 100 build trusted, reliable, compliant software. Customers who use Sonar are 44% less likely to report an outage due to AI-generated code.

We believe code verification is the critical missing link in the Agent-Centric Development Cycle (AC/DC). Industry giants like Nvidia, ServiceNow, Booking.com, Goldman Sachs, AstraZeneca, and Ford Motor Company count on us to provide independent, explainable, consistent review and governance of their AI-generated code via products like:

SonarQube: The world’s leading AI code review and verification platform.
SonarQube Foundation Agent: Currently topping the leaderboards for agentic software repair.
SonarSweep & Sonar Context Augmentation: Providing the enterprise-grade context and constraints agents need to be truly effective.

Our team operates across global hubs in Austin, Bochum, Dubai, Geneva, London, Singapore, Tokyo, and Washington D.C. We move with a mindset we call CODE:

Committed to our customers and community.
Obsessed with quality.
Deliberate in our decisions.
Effective as one team.

With over $400M in revenue and profitable, fast-paced growth, we are building the backbone of the AI software revolution. If you’re hungry to have an impact, want to build at a fast pace, and ready to work at the forefront of AI, we want to hear from you.

Position description

This role is the data team's dedicated analytical partner for Marketing. Your core job is to turn marketing data into decisions: diagnose what is working and what is not, explain why, and recommend where to spend the next dollar. You will own marketing attribution, ROI, and conversion analysis end to end, and you will be proactive about it, surfacing findings and opportunities before anyone asks.

You will explore data, form hypotheses, and partner with our Data and Analytics Engineers to shape the models and pipelines you need. You will help define those models, but your primary measure of success is the quality and impact of your analysis.

This role sits in the Data & Insights team and partners closely with Marketing, IT/Marketing Ops, Data Engineers, Analytics Engineers, and data scientists covering other domains.

What you will do

Drive marketing decisions with analysis. Own attribution, ROI, conversion, and funnel analysis. Diagnose drops and anomalies, quantify what drives them, and translate findings into clear recommendations for marketing leaders.
Optimize marketing spend. Connect spend to outcomes across channels and campaigns, and advise on where to invest, cut, or test next.
Be proactive. Explore and correlate data to surface insights nobody asked for. Anticipate the next question. Bring opportunities to the marketing team rather than waiting for requests.
Run experiments. Design and read out A/B tests and other experiments, applying sound statistical methods and being honest about significance and causality.
Partner on the data foundation. Work hand in hand with Data Engineers and Analytics Engineers to get marketing data into the warehouse and modeled. Define requirements, explore raw data, and contribute to data models that connect marketing data with sales and product data.
Tell the story. Communicate insights so non-technical stakeholders can act, and document context, caveats, and decisions so the work survives handoffs.

Experience and qualifications

Strong analytical track record: someone who has measurably influenced business or marketing decisions through analysis, not just produced reports.
Comfort with the latest AI tools, and a habit of using them to work faster and sharper: exploring data, writing and debugging code, drafting analysis, and accelerating insight. You stay current as the tooling evolves and bring new approaches to the team.
Eagerness to develop: you actively grow your skills, seek feedback, and treat new tools and methods as opportunities rather than threats.
Solid SQL. You can independently query, join, and explore data without waiting for someone to prepare it for you.
Proficiency in Python for analysis, modeling, and automation.
Statistical foundation: experimentation, significance testing, regression, segmentation, forecasting, and the judgment to know which applies.
Working knowledge of marketing and GTM data: channels, campaigns, attribution models, funnel and conversion metrics, and the realities of joining marketing data to CRM/sales and product usage data.
Willingness to get hands-on with data modeling. You don't need to be a dbt expert, but you must be comfortable exploring messy data and partnering on (or building) the models you need rather than waiting for clean tables.
Strong communication and stakeholder skills: you can challenge weak measurement respectfully and make a recommendation, not just present options.
Proactivity and autonomy: you raise your hand early, plan your own work, and look for impact without being asked.

In-office culture

We're intentional about this. We believe the best teams are built in the room together. Three anchor days — Mondays, Tuesdays, and Thursdays — create the collaboration rhythm that makes a hub office worth having.

Candidates need to be genuinely based in the location the role is posted — if that's not where you are today, we're happy to support relocation for the right person.

We value diversity, equity, and inclusion

At Sonar, we believe that our diversity is our strength. We are a global company that values and respects different backgrounds, perspectives, and cultures. We are committed to fostering a diverse and inclusive work environment where everyone feels valued and empowered to contribute their best. We are proud to be an equal opportunity employer and welcome all qualified applicants, regardless of race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.

If you need any accommodation, please reach out to us at [email protected].

All offers of employment at Sonar are contingent upon the results of a comprehensive background check and reference verification conducted before the start date.

Applications that are submitted through agencies or third party recruiters will not be considered.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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Data Scientist, Marketing Analytics

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