Data Scientist - AI & Experimentation

Jobgether; España; Remote; EUR 42,000 - 75,000; Full time

Benefits offered by this job

Remote work arrangement

Permanent employment

Office access Berlin-Mitte (optional)

Open and collaborative culture

Regular feedback conversations

Startup mindset

Job summary

Jobgether is seeking a Data Scientist - AI & Experimentation to work remotely from Spain. You will combine statistical modeling, ML, and experimentation to improve a healthcare job-matching platform, building predictive models and AI-powered features while designing experiments that shape product strategy.

You will collaborate with product, engineering, and marketing to process large datasets, optimize matching, and translate analyses into measurable business outcomes.

Qualifications

• Strong knowledge of statistics, justify methods and interpret results.
• Advanced Python (pandas, scikit-learn, NumPy) and SQL skills.
• Experience applying data science techniques to real-world problems.
• Hands-on ML model deployment and AI solution implementation.
• Experience with LLMs and RAG systems in production contexts.
• Solid understanding of A/B testing and experimentation pitfalls.
• Familiarity with performance marketing metrics (CAC, ROAS).
• Experience in Jira or similar project tracking tools.
• Quantitative degree is advantageous.

Responsibilities

• Develop, validate, and deploy statistical and predictive models for pricing and matching.
• Build and improve LLM-powered features, including RAG pipelines.
• Design prompt engineering and evaluation workflows for AI outputs.
• Translate business questions into testable hypotheses and design experiments.
• Analyze conversion funnels and user journeys to improve healthcare matching.
• Collaborate with product, engineering, and marketing to drive impact.
• Define KPIs and build dashboards using AWS QuickSight.
• Track model performance, experiment outcomes, and business impact.
• Document projects and communicate progress via Jira.
• Present findings and actionable recommendations to stakeholders.

Skills

Statistics

Python (pandas, scikit-learn, NumPy)

SQL

Data science

Experiment design

A/B testing

LLMs / RAG

Performance marketing metrics

Jira

Education

Quantitative degree preferred

Tools

Jira

AWS QuickSight

Job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Data Scientist - AI & Experimentation based remotely in Spain.

We are looking for a data-driven Data Scientist to combine statistical modeling, machine learning, and experimentation to improve a digital job-matching platform in the healthcare recruitment sector. In this role, you will develop predictive models, enhance AI-powered features, and design experiments that directly influence product strategy and business performance. You will work with large datasets to understand user behavior, optimize matching between supply and demand, and uncover opportunities for growth. From LLM-powered applications and Retrieval-Augmented Generation (RAG) systems to A/B testing and marketing analytics, your work will move beyond analysis into practical implementation. Collaborating with product, engineering, and marketing teams, you will turn complex findings into measurable business outcomes. This is an opportunity to take end-to-end ownership of data initiatives in a collaborative, fast-moving environment where analytical rigor and real-world impact matter.

Accountabilities:

• Develop, validate, and deploy statistical and predictive models that inform pricing, job matching, and growth decisions.
• Build and improve LLM-powered product features, including Retrieval-Augmented Generation (RAG) pipelines and applications of emerging AI technologies.
• Design prompt engineering and evaluation workflows to assess AI output quality, monitor reliability, and identify performance regressions before they affect users.
• Translate business questions into testable hypotheses and design experiments, including A/B tests, that support clear, evidence-based decisions.
• Analyze conversion funnels and user journeys to identify drop-off points, uncover friction, and improve matching between healthcare professionals and employers.
• Partner with performance marketing teams to optimize audience targeting, attribution, and campaign efficiency.
• Define meaningful key performance indicators (KPIs) and build dashboards and monitoring systems using tools such as AWS QuickSight.
• Track model performance, experiment outcomes, and business impact to ensure data initiatives deliver measurable results.
• Document projects, prioritize tasks, and communicate progress transparently through Jira and other collaborative workflows.
• Present findings and actionable recommendations to stakeholders across product, engineering, and marketing.
• Follow through on recommendations to support implementation and measure their impact after deployment.

Requirements:

• Strong knowledge of statistics, including the ability to select appropriate methods, justify assumptions, and interpret results critically.
• Advanced proficiency in Python, particularly pandas, scikit-learn, and NumPy, as well as strong SQL skills.
• Demonstrated experience applying statistical analysis and data science techniques to real-world business problems.
• Hands-on experience taking machine learning models and modern AI solutions from initial concept through implementation and practical use.
• Practical experience with LLMs and RAG systems in production or near-production environments, including prompt engineering, retrieval quality, and output evaluation.
• Solid understanding of A/B testing, including sample size estimation, statistical significance, common experimental pitfalls, and situations where experimentation may not be appropriate.
• Working knowledge of performance marketing metrics and concepts, including Customer Acquisition Cost (CAC), Return on Ad Spend (ROAS), and marketing attribution.
• Project experience in at least one of the following areas: anomaly detection, trend analysis, marketing mix modeling, or multi-touch attribution.
• Experience in e-commerce, online marketplaces, or other platform-based businesses, ideally involving supply-and-demand dynamics.
• Strong analytical thinking, problem-solving abilities, and attention to data quality.
• Ability to communicate complex findings clearly, make practical recommendations, and collaborate effectively with cross-functional stakeholders.
• Experience documenting work, managing priorities, and tracking projects using Jira or similar tools.
• A degree in mathematics, statistics, physics, computer science, or another quantitative discipline is an advantage.

Benefits:

• Annual salary ranging from €42,000 to €75,000.
• Permanent employment opportunity.
• Remote work arrangement, with a home-office option.
• Flat organizational structure, short decision-making processes, and a start-up mindset.
• Open and collaborative company culture with supportive, communicative colleagues.
• Regular feedback conversations to encourage professional development.
• Access to a centrally located office in Berlin-Mitte, with an open-plan working environment.
• Complimentary drinks at the office.
• Opportunity to work on practical AI, machine learning, and experimentation projects with a direct impact on product and business performance.

Data Privacy Notice:

By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

How Jobgether works:

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!