Job details
● 💼 Engineering Team
● 📍 Spain - Barcelona
● 🕜 Full-Time/Remote

What you will do

As a Junior Data Science Engineer, you will join our core AI team to tackle some of the most complex challenges in hospitality tech. You will be focusing on developing new methods of artificial intelligence, not just using existing ones. You will help expand our AI capabilities, contributing to machine learning and causal inference systems that optimize everything from pricing strategies to user engagement across thousands of hotel websites. This is a unique opportunity to transform abstract mathematical problems into tangible, high-impact products that shape the next generation of intelligent tools for our clients.

Where you will have impact

• Develop and implement machine learning algorithms and causal inference systems to solve unique industry problems from the ground up.
• Contribute to the core AI of flagship products, including our intelligent agent systems.
• Design and build predictive models that optimize conversion, personalization, and pricing strategies for our global hotel partners.
• Collaborate on creating new products from scratch, such as dynamic discount management systems designed to maximize hotel revenue.
• Work closely with the team to maintain and improve the performance of our extensive portfolio of live data science products.
• Translate complex data and model outputs into actionable strategies that drive our clients' commercial success.
• Engage in deep, collaborative problem-solving sessions to devise creative solutions for uncharted challenges in AI.

About Our Team

You'll be joining our Data Science team, the curious and analytical minds behind Lighthouse's AI and machine learning capabilities. We are a group of proactive thinkers who own the scientific development of products central to the company's strategy. Our focus is evolving from traditional predictive ML toward more advanced AI systems, including LLM-powered tools, recommendation engines, and agentic workflows. We focus on turning complex, abstract ideas into real-world applications and collaborate closely with the Product, Engineering, and Data teams to push the industry forward.

What's in it for you?

• Flexible time off: Autonomy to manage your work-life balance.
• Alan Flex benefits: 160€/month for food or nursery.
• Flexible retribution: Optional benefits through tax-free payroll deductions for food, transportation and/or nursery. 
• Wellbeing support: Subsidized ClassPass subscription.
• Comprehensive health insurance: 100% Alan coverage for you, your spouse, and dependents.
• Impactful work: Shape products relied on by 85,000+ users worldwide.
• Referral bonuses: Earn rewards for bringing in new talent.

Who you are

• A strong quantitative and analytical background, ideally with a degree in Mathematics, Statistics, Data Science, Computer Science, Physics, or a similar discipline.
• A solid, foundational understanding of Machine Learning, statistics, and data modeling principles.
• Strong programming skills in Python, including familiarity with core data science libraries like pandas, numpy, scikit-learn, and PyTorch/TensorFlow.
• A proactive and hands-on mindset with a genuine passion for AI, machine learning, and building intelligent systems.
• Excellent problem-solving abilities and the capacity to work independently on complex technical challenges.
• A quick learner with the ability to adapt to fast-evolving technologies and product needs.
• Strong communication and collaboration skills, with an eagerness to contribute within a technical team.
• Full fluency in written and spoken English. 

We welcome

• Experience with LLMs, RAG systems, agentic workflows, causal inference, or recommender systems.
• Familiarity with our infrastructure stack, including AWS, Docker, Kubernetes, Airflow, or Apache Kafka.
• Prior experience building AI products or working in a SaaS or hospitality environment.

Technologies you will work with

 Pandas, NumPy, Scikit-Learn, PyTorch, TensorFlow, FastAPI, Apache Kafka, Airflow, AWS, Docker, Kubernetes, GitHub.

Why Engineering at Dataiku?

Dataiku’s on-premise, cloud, or SaaS-deployed platform connects many data science technologies, and our technology stack reflects our commitment to quality and innovation. We integrate the best of data and AI tech, selecting tools that truly enhance our product. From the latest LLMs to our dedication to open source communities, you'll work with a dynamic range of technologies and contribute to the collective knowledge of global tech innovators. You can find out even more about working in Engineering at Dataiku by taking a look here.

Here are some useful links so you preview what we do at Dataiku: Dataiku's Key Capabilities ; Dataiku's Github, you can also take a look at the Gallery, a public instance showcasing some example projects (note editing is very limited and will be regularly reset). 

Our product is called Dataiku DSS which stands for Dataiku Data Science Studio. If you’d like to know more about it, you can watch the demo here or try the free version here.

How you’ll make an impact

This position is either onsite/hybrid from our Berlin office or full remote from any part of Germany.

As a Fullstack Engineer, you’ll contribute to building Dataiku DSS core features by joining one of the following themes:

• Data Preparation: Develop tools for data integration, transformation, and cataloging, as well as Jupyter notebooks, SQL workbenches, and APIs.
  • Add new capabilities for data integration, transformation, and visualization using LLMs
  • Optimize workflows for large-scale datasets and improve database support
  • Strengthen developer tools like Jupyter notebooks and SQL workbenches
  • Tech stack: Java, Python, AngularJS, Angular

• AI & Machine Learning: Collaborate on next-gen AI features, from statistics and time series forecasting to LLM inference.
  • Build next-generation features like cross-provider LLM APIs or integration with the latest Machine Learning models
  • Collaborate with research teams on innovative machine learning experiments
  • Tech stack: Python, scikit-learn, TensorFlow, PyTorch, Java, Angular, AngularJS

• Data Consumption: build the experience that makes data accessible and actionable for everyone.
  • Enhance our collaborative Workspaces to organize and explore charts, dashboards, datasets and more
  • Create innovative interfaces that answer business questions and surface relevant insights using LLMs
  • Tech stack: Angular, AngularJS, Java, Python

• Data Visualization: elevate our data visualization capabilities with high-performance charting tools and dashboards.
  • Develop new chart types and optimize visualization performance
  • Enhance dash boarding capabilities to deliver fast and flexible experiences
  • Tech stack: React, AngularJS, Angular, D3.js, ECharts, Node.js, Java, Spring
    
    
• MLOps: Develop back-end capabilities for automating and monitoring ML model lifecycles while supporting cross-functional collaboration.
  • Build tools to automate retraining, monitoring, and deployment of ML models
  • Enhance collaboration features for ML stakeholders
  • Tech stack: Python, Java, Angular, Angular.JS, Kubernetes, Docker
    
    
• Platform: Focus on scaling and securing the platform while improving cloud integrations and supporting a wide array of data sources and engines.
  • Optimize processing engines for scalability and latency
  • Expand capabilities to support new databases and cloud platforms
  • Tech stack: Java, Python, Angular, Kubernetes, Spark, AWS, Azure, GCP
    
    
• AI Governance: Build features for AI compliance, connecting disparate systems and simplifying governance processes.
  • Develop customizable platforms for managing AI compliance and governance
  • Simplify policy enforcement and integration across disparate systems
  • Tech stack: Java, Angular, PostgreSQL

What you need to be successful 

• We’re stack agnostic, so all you need is a significant experience in software engineering,  building a real product
• We’re hiring at all levels (junior, mid, senior)
• A passion for combining backend performance with exceptional frontend user experience.
• You want to work in a fast-paced, high-growth environment that values diversity of talent, excellence of product, and exciting engineering challenges at scale

What does the hiring process look like?

• Initial call with a member of our Technical Recruiting team (45min)
• Video call with an Engineering Team Lead (1h30)
• Technical Assessment to show your skills (Home Test or Live Coding)
• Final Interviews with our VPs of Engineering (2h)   #LI-Remote

Highlights:

Location: Spain, Remote

Language: Russian-speaking team; Professional working proficiency in English (B1 or higher)

About Us

Fundraise Up is a modern fundraising platform built to make donating to nonprofits as fast and convenient as possible. We continuously innovate to reduce page load times, boost conversion rates, and support a wide range of payment methods. Each month, people around the world contribute tens of millions of dollars through our platform.

The world’s leading nonprofit organizations trust Fundraise Up. UNICEF, the most prominent UN charity, uses our platform for 100% of its online fundraising. So does the American Heart Association, the Alzheimer’s Association, and many others. We’re proud to maintain a 4.9 out of 5 rating on leading review platforms.

We serve the enterprise segment, with a primary client base in the US, Canada, UK, and Australia.

The Team

Our product development team is currently at 150+ and growing. Team members are located across Spain, Serbia, Poland, Portugal, Turkey, Cyprus, Georgia and Armenia. We primarily communicate in Russian.

We’re a tight-knit, high-impact team where every task matters. It’s a dynamic, collaborative environment where smart, curious engineers support one another, share knowledge, and strive for excellence. We encourage open dialogue and host bi-weekly engineering meetups to explore technical topics and showcase team insights.

About the Role

We’re looking for a Team Lead to join our Product Analytics team for the New Products direction. The New Products direction is our “internal incubator,” responsible for the company’s future revenue. We don’t just improve existing products — we launch entirely new business verticals from scratch.

Currently, we have three key focus areas:
    1.    P2P (Peer-to-Peer): Building tools for mass fundraising events and marathons (a market with $8M+ ARR potential).
    2.    Tap-to-Pay & Kiosks: Enabling offline donations via smartphones and physical terminals.
    3.    Major Donors: Leveraging AI to identify and engage high-value donors.

At the moment, the team consists of one analyst who has already started working on the P2P product.

What You’ll Do

• Act as a right hand to product leads (PMs): help define success criteria for pilots and evaluate whether new products gain traction
• Build analytics from scratch: design data collection systems and ensure reliability monitoring from day one
• Evaluate the performance of new product launches
• Lead and grow the team: mentor team members, run 1:1s, and establish processes in a fast-growing function, as well as plan the roadmap and oversee execution and timelines

Requirements

• 5+ years of experience as a Product Analyst
• 2+ years of team management experience
• Strong knowledge of mathematical statistics and probability theory
• Proficiency in Python (NumPy, pandas, matplotlib, seaborn, scikit-learn)
• Advanced SQL skills
• Experience with BI tools (Tableau, Power BI, Metabase)

Our Tech Stack

• Python
• ClickHouse, MongoDB, PostgreSQL
• Tableau, Grafana
• Airflow
• Git

Bonus points

• Curiosity and a hypothesis-driven mindset
• Ability to communicate complex analytical concepts to non-technical audiences
• Detail-oriented with a strong sense of ownership
• Comfort working in fast-paced, data-rich environments

Why work with us

• A strong, collaborative product team that owns what it builds
• Clear product vision and access to real customer feedback from global nonprofit leaders
• Flat structure: no politics, just great work with great people
• Transparent company culture-we share how we’re growing, where revenue comes from, and what’s next
• Long-term focus: we offer equity options and value sustained, meaningful contribution

Benefits

• 31 days off
• 100% paid telemedicine plan
• Home Office Setup Assistance: the company offers assistance with purchasing furniture (office chair, office desk, monitor) and other items to create a comfortable workspace.
• English learning courses
• Relevant professional education
• Gym or swimming pool
• Co-working
• Remote working
• Relocation package

_{**Please note: All official correspondence from Fundraise Up will exclusively originate from the @fundraiseup.com domain. Exercise caution and ensure the authenticity of emails claiming to be from our company.}

Highlights:

Location: Spain, Remote

Language: Russian-speaking team; Professional working proficiency in English (B1 or higher)

About Us

Fundraise Up is a modern fundraising platform built to make donating to nonprofits as fast and convenient as possible. We continuously innovate to reduce page load times, boost conversion rates, and support a wide range of payment methods. Each month, people around the world contribute tens of millions of dollars through our platform.

The world’s leading nonprofit organizations trust Fundraise Up. UNICEF, the most prominent UN charity, uses our platform for 100% of its online fundraising. So does the American Heart Association, the Alzheimer’s Association, and many others. We’re proud to maintain a 4.9 out of 5 rating on leading review platforms.

We serve the enterprise segment, with a primary client base in the US, Canada, UK, and Australia.

The Team

Our product development team is currently at 150+ and growing. Team members are located across Spain, Serbia, Poland, Portugal, Turkey, Cyprus, Georgia and Armenia. We primarily communicate in Russian.

We’re a tight-knit, high-impact team where every task matters. It’s a dynamic, collaborative environment where smart, curious engineers support one another, share knowledge, and strive for excellence. We encourage open dialogue and host bi-weekly engineering meetups to explore technical topics and showcase team insights.

About the Role

We’re looking for a Product Analyst to join the Donor Portal (Donor Experience) team. The Donor Portal team owns the post-donation experience – everything that happens after a donor completes a donation. The team focuses on reducing churn and increasing subscription LTV by improving subscription management within the donor portal (pauses, amount changes, skipping charges, etc.), as well as enhancing donor communications via email.

What You’ll Do

• Run A/B tests
• Identify insights in data, conduct research, and help product teams uncover growth opportunities.
• Work with retention rate and subscription/supporter LTV metrics.
• Design and build data marts.
• Develop and maintain BI dashboards.
• Handle ad-hoc requests from product teams.

Requirements

• 5+ years of professional experience as a Data Analyst or Product Analyst.
• A strong foundation in mathematical statistics and probability theory.
• Advanced proficiency in SQL.
• Expertise in Python and its data analysis libraries (NumPy, Pandas, Matplotlib, Scikit-learn).
• Hands-on experience with BI tools (Tableau, Power BI, Metabase).
• Strong written English for clear documentation and communication.
• A proactive, detail-oriented mindset with a passion for solving complex problems.

Our Tech Stack

• Languages & Libraries: Python
• Databases: ClickHouse, MongoDB, PostgreSQL
• BI & Visualization: Tableau, Grafana
• Orchestration: Airflow
• Version Control: Git

Bonus points

• Curiosity and a hypothesis-driven mindset
• Ability to communicate complex analytical concepts to non-technical audiences
• Detail-oriented with a strong sense of ownership
• Comfort working in fast-paced, data-rich environments

Why work with us

• A strong, collaborative product team that owns what it builds
• Clear product vision and access to real customer feedback from global nonprofit leaders
• Flat structure: no politics, just great work with great people
• Transparent company culture-we share how we’re growing, where revenue comes from, and what’s next
• Long-term focus: we offer equity options and value sustained, meaningful contribution

Benefits

• Private medical insurance for the employee and their family
• 23 paid vacation days per year
• 11 paid public holidays per year
• 5 company-paid sick leave days
• English learning courses
• Relevant professional education
• Gym or swimming pool
• Home Office Setup Assistance: the company offers assistance with purchasing furniture (office chair, office desk, monitor) and other items to create a comfortable workspace
• Co-working
• Remote working

_{**Please note: All official correspondence from Fundraise Up will exclusively originate from the @fundraiseup.com domain. Exercise caution and ensure the authenticity of emails claiming to be from our company.}

Highlights:

Location: Spain, Remote

Language: Russian-speaking team; Professional working proficiency in English (B1 or higher)

About Us

Fundraise Up is a modern fundraising platform built to make donating to nonprofits as fast and convenient as possible. We continuously innovate to reduce page load times, boost conversion rates, and support a wide range of payment methods. Each month, people around the world contribute tens of millions of dollars through our platform.

The world’s leading nonprofit organizations trust Fundraise Up. UNICEF, the most prominent UN charity, uses our platform for 100% of its online fundraising. So does the American Heart Association, the Alzheimer’s Association, and many others. We’re proud to maintain a 4.9 out of 5 rating on leading review platforms.

We serve the enterprise segment, with a primary client base in the US, Canada, UK, and Australia.

The Team

Our product development team is currently at 150+ and growing. Team members are located across Spain, Serbia, Poland, Portugal, Turkey, Cyprus, Georgia and Armenia. We primarily communicate in Russian.

We’re a tight-knit, high-impact team where every task matters. It’s a dynamic, collaborative environment where smart, curious engineers support one another, share knowledge, and strive for excellence. We encourage open dialogue and host bi-weekly engineering meetups to explore technical topics and showcase team insights.

About the Role

As a Product Analyst, you will be a versatile data expert at the heart of our product decisions. Your work will span the full analytical lifecycle—from building data marts and ETL processes to designing and analyzing A/B tests and delivering key insights to stakeholders. This is a role for a proactive analyst who is comfortable working across a wide range of tasks and is passionate about using data to find the truth and drive results.

What You’ll Do

• Uncover Actionable Insights: Identify key trends in user behavior, develop data-backed product hypotheses, and work with teams to test them.
• Own A/B Testing: Design, launch, and analyze A/B tests to validate ideas and optimize product performance.
• Build a Data Foundation: Create and maintain data marts and BI reports to visualize product and operational metrics for the entire company.
• Perform Deep-Dive Analyses: Handle ad-hoc analytical requests to answer critical business and product questions.

Requirements

• 5+ years of professional experience as a Data Analyst or Product Analyst.
• A strong foundation in mathematical statistics and probability theory.
• Advanced proficiency in SQL.
• Expertise in Python and its data analysis libraries (NumPy, Pandas, Matplotlib, Scikit-learn).
• Hands-on experience with BI tools (Tableau, Power BI, Metabase).
• Strong written English for clear documentation and communication.
• A proactive, detail-oriented mindset with a passion for solving complex problems.

Our Tech Stack

• Languages & Libraries: Python
• Databases: ClickHouse, MongoDB, PostgreSQL
• BI & Visualization: Tableau, Grafana
• Orchestration: Airflow
• Version Control: Git

Bonus points

• Curiosity and a hypothesis-driven mindset
• Ability to communicate complex analytical concepts to non-technical audiences
• Detail-oriented with a strong sense of ownership
• Comfort working in fast-paced, data-rich environments

Why work with us

• A strong, collaborative product team that owns what it builds
• Clear product vision and access to real customer feedback from global nonprofit leaders
• Flat structure: no politics, just great work with great people
• Transparent company culture-we share how we’re growing, where revenue comes from, and what’s next
• Long-term focus: we offer equity options and value sustained, meaningful contribution

Benefits

• Private medical insurance for the employee and their family
• 23 paid vacation days per year
• 11 paid public holidays per year
• 5 company-paid sick leave days
• English learning courses
• Relevant professional education
• Gym or swimming pool
• Home Office Setup Assistance: the company offers assistance with purchasing furniture (office chair, office desk, monitor) and other items to create a comfortable workspace
• Co-working
• Remote working

_{**Please note: All official correspondence from Fundraise Up will exclusively originate from the @fundraiseup.com domain. Exercise caution and ensure the authenticity of emails claiming to be from our company.}

Highlights

Location: Spain, Remote

Language: Russian-speaking team; English proficiency required (C1)

About Us

Fundraise Up is a modern fundraising platform built to make donating to nonprofits as fast and convenient as possible. We continuously innovate to reduce page load times, boost conversion rates, and support a wide range of payment methods. Each month, people around the world contribute tens of millions of dollars through our platform.

The world’s leading nonprofit organizations trust Fundraise Up. UNICEF, the most prominent UN charity, uses our platform for 100% of its online fundraising. So does the American Heart Association, the Alzheimer’s Association, and many others. We’re proud to maintain a 4.9 out of 5 rating on leading review platforms.

We serve the enterprise segment, with a primary client base in the US, Canada, UK, and Australia.

The Team

Our product development team is currently at 150+ and growing. Team members are located across Spain, Serbia, Poland, Portugal, Turkey, Cyprus, Georgia and Armenia. We primarily communicate in Russian.

We’re a tight-knit, high-impact team where every task matters. It’s a dynamic, collaborative environment where smart, curious engineers support one another, share knowledge, and strive for excellence. We encourage open dialogue and host bi-weekly engineering meetups to explore technical topics and showcase team insights.

About the Role

As a Product Analyst, you will be a critical partner to our business teams, working closely with Sales, Marketing, Customer Success (CSM), and Partnerships. Your core mission is to transform raw data into actionable insights that measure effectiveness, drive strategy, and inform the product roadmap. While our development team is Russian-speaking, our main audience and business stakeholders are in the U.S., making your fluency in English essential for success.

What You’ll Do

• Uncover critical insights by forming hypotheses and validating them with data.
• Identify global and local trends in user behavior to inform product decisions.
• Analyze and interpret customer metrics to measure impact and value.
• Design and evaluate A/B tests with prospective customers to optimize performance.
• Handle ad-hoc analytical requests from stakeholders across the organization.

Requirements

• 4+ years of experience as a Data Analyst or Product Analyst.
• A strong foundation in mathematical statistics and probability theory.
• Advanced proficiency in SQL.
• Expertise in Python and its data analysis libraries (NumPy, Pandas, Matplotlib, Scikit-learn).
• Hands-on experience with BI tools (Tableau, Power BI, Metabase).
• Excellent command of written and spoken English (C1 level or higher).
• A proactive, curious mindset with strong analytical and communication skills.

Our Tech Stack

• Languages & Libraries: Python
• Databases: ClickHouse, MongoDB, PostgreSQL
• BI & Visualization: Tableau, Grafana, Metabase
• Orchestration: Airflow
• Version Control: Git

Bonus points

• Curiosity and a hypothesis-driven mindset
• Ability to communicate complex analytical concepts to non-technical audiences
• Detail-oriented with a strong sense of ownership
• Comfort working in fast-paced, data-rich environments

Why work with us

• A strong, collaborative product team that owns what it builds
• Clear product vision and access to real customer feedback from global nonprofit leaders
• Flat structure: no politics, just great work with great people
• Transparent company culture-we share how we’re growing, where revenue comes from, and what’s next
• Long-term focus: we offer equity options and value sustained, meaningful contribution

Benefits

• Private medical insurance for the employee and their family
• 23 paid vacation days per year
• 11 paid public holidays per year
• 5 company-paid sick leave days
• English learning courses
• Relevant professional education
• Gym or swimming pool
• Home Office Setup Assistance: the company offers assistance with purchasing furniture (office chair, office desk, monitor) and other items to create a comfortable workspace
• Co-working
• Remote working

_{**Please note: All official correspondence from Fundraise Up will exclusively originate from the @fundraiseup.com domain. Exercise caution and ensure the authenticity of emails claiming to be from our company.}

The role

We seek an experienced Specialist Solutions Architect to support AI-focused customers leveraging Nebius services. In this role, you will be a trusted advisor, collaborating with clients to design scalable AI solutions, resolve technical challenges and manage large-scale AI deployments involving hundreds to thousands of GPUs.

You’re welcome to work on-site in Amsterdam or remotely from any other EU country.

Your responsibilities will include:

• Designing customer-centric solutions that maximize business value and align with strategic goals.
• Building and maintaining long-term relationships to foster trust and ensure customer satisfaction.
• Delivering technical presentations, producing whitepapers, creating manuals and hosting webinars for audiences with varying technical expertise.
• Collaborating with engineering and product teams to effectively prioritize and relay customer feedback.

We expect you to have:

• 3+ years of experience with cloud technologies in MLOps engineering, Machine Learning engineering or similar roles.
• Strong understanding of ML ecosystems, including models, use cases and tooling.
• Proven experience in setting up and optimizing distributed training pipelines across multi-node and multi-GPU environments.
• Hands-on knowledge of frameworks like PyTorch or JAX.
• Excellent verbal and written communication skills.

It will be an added bonus if you have:

• Expertise in deploying inference infrastructure for production workloads.
• Ability to transition ML pipelines from POC to scalable production systems.

Preferred tooling:

• Programming Languages – Python, Go, Java, C++
• Orchestration – Kubernetes (K8s), Slurm
• DevOps Tools – Git, Docker, Helm
• Infrastructure as Code (IaC) – Terraform
• ML Frameworks and Libraries – PyTorch, TensorFlow, JAX, HuggingFace, Scikit-learn

About the Role

At SumUp, we're on a mission to empower small businesses across the globe by providing a vast set of simple and affordable business tools to help them start, run, and grow their businesses. Lending at SumUp is a mature, scaled business with a strong and proven credit risk foundation. Our core models and decisioning frameworks are already robust and in production; as our portfolio grows, our challenge is safely extracting marginal gains from a complex system where changes are incremental and the stakes are high. As a Senior Data Scientist, you will be highly hands-on and embedded in day-to-day lending decisions. This role exists to strengthen our ability to improve what already works, reduce operational risk, and ensure long-term reliability as we scale into new markets. You will work within the Credit Risk Analytics (CRA) team, a streamlined group responsible for the modeling and analytics that underpin our global lending portfolio.

What you’ll do

• Optimise Credit Risk Models: Iterate on existing models to improve stability, predictive power, and net revenue impact while performing deep dives to support risk decisions.
• Drive End-to-End Deployment: Develop, test, and deploy new model versions in close collaboration with Credit Risk Engineering (CRE), ensuring no regressions or operational issues.
• Enhance ML Infrastructure: Improve machine learning pipelines and workflows to reduce maintenance overhead and failure modes.
• Integrate New Data: Evaluate and integrate new internal and external data sources (e.g., credit bureaus, open banking) into existing models and processes.
• Monitor Performance: Closely monitor models in production, investigating performance shifts or anomalies to maintain portfolio integrity.
• Promote Technical Excellence: Document work clearly and participate in code reviews, design discussions, and pair programming to maintain high-quality standards.

What makes you great for this position

• 5+ years of experience as a Data Scientist (or 7+ years in data-related/software engineering fields with at least 3 years in Data Science).
• MUST HAVE experience working with Credit Risk. 
• Deep understanding of Data Science principles, including statistics, probability theory, and machine learning concepts.
• Strong experience with Python (pandas, PySpark, scikit-learn) and SQL for complex data retrieval and manipulation
• Proven track record of building, evaluating, and deploying machine learning models end-to-end at scale.
• Experience with credit risk assessment, lending, or financial decisioning models.
• Strong software engineering practices, including writing clean, maintainable, testable code with version control and documentation.
• Collaborative and respectful team player who is comfortable voicing disagreements while committing to team decisions ("disagree and commit").
• Fluency in English with the ability to communicate technical findings clearly to diverse stakeholders.

Why you should join SumUp

🌎 Opportunity to work with SumUppers globally on large-scale fintech products used by millions of businesses worldwide, from our Barcelona office.

🌈 Commitment to Diversity and Inclusion: be part of a workplace that values and promotes diversity, fostering an inclusive environment where everyone's perspectives are respected and embraced.

🚀 Enrolment onto our Virtual Stock Option programme: you will own a stake in SumUp’s future success.

📚 A dedicated annual L&D budget of €2000 for your individual development, which you can be used to attend conferences and/or advancing your career through further education.

💶 A corporate pension scheme where we match up to 20% of your contributions.

🏖️ Generous time off: enjoy 28 days of paid leave plus public holidays and special leave days.

🚵🏾‍♂️ Numerous other benefits such as Urban Sports Club subsidy, Kita placement assistance, subsidised office lunches.

🌴 Break4me: 1-month sabbatical after 3 years of service.

🔗 Referral Bonus: earn additional rewards by referring talented individuals to join the SumUp team.

About SumUp

Be empowered to do more that matters. At SumUp, we're on a mission to empower small businesses across the globe by providing a vast set of simple and affordable business tools to help them start, run, and grow their businesses. Today, over 4 million businesses in 36 markets rely on SumUp as their financial partner to manage payments, finance and customer relationships.

Our commitment to small businesses is reflected in our diverse team of over 3,000 SumUppers from over 90 nationalities, united by global collaboration and an innovative mindset. Our core values lay the foundation for who we are and what we stand for, shaping our work culture and driving our success. We foster an inclusivity and continuous learning culture, providing a safe space for personal and professional growth. Our differences make us unique and strong as we strive to create an environment where everyone belongs and feels supported, no matter how they identify.

SumUp is proud to be an Equal Employment Opportunity employer, actively seeking and embracing diversity in our workforce. We don't make hiring or employment decisions based on race, colour, religion or religious belief, ethnic or national origin, nationality, sex, gender, gender identity, sexual orientation, disability, age or any other basis protected by applicable laws or prohibited by company policy. Our commitment extends beyond recruitment to creating a safe and respectful workplace where harassment of any form is strictly prohibited.

We are now expanding our data capabilities and seeking an experienced Head / Director of Data Science to lead and scale our Data Science UA team function in Barcelona.

This role is ideal for a leader with a strong technical background, excellent people-management skills, and the ability to turn data into actionable, high-impact product and business outcomes.

Role Overview:

The Head / Director of Data Science will be responsible for building and growing our Data Science organization, driving advanced analytics and ML initiatives, and ensuring our products and business units are empowered by high-quality insights and predictive capabilities.

You will work closely with Product, Engineering, Revenue, and Leadership teams to translate business needs into DS/ML solutions, strengthen our data infrastructure, and support decision-making across the ecosystem.

This is a strategic and hands-on leadership role with significant influence on product evolution, optimization algorithms, and operational excellence.

Key Responsibilities:

Leadership & Strategy

• Lead and scale the Data Science function across the organization.
• Translate business and product goals into clear DS/ML initiatives and execution plans.
• Build and promote a strong data-driven culture across all teams.
• Applied Data Science & ML.
• Oversee development, deployment, and monitoring of ML models across Appodeal’s product and monetization ecosystem.
• Guide experimentation, modeling, uplift measurement, and algorithmic optimization.
• Ensure model quality, reliability, fairness, and performance at scale.
• Collaboration & Stakeholder Management.
• Partner with Product and Engineering teams to integrate Data Science into product roadmaps.
• Work with business units to identify opportunities, define DS/ML requirements, and deliver impactful insights.
• Communicate DS outcomes, metrics, and recommendations to leadership.

Team Leadership

• Lead, mentor, and develop a multidisciplinary team of Data Scientists, Analysts, and ML/AI specialists.
• Foster knowledge sharing, best practices, experimentation, and continuous improvement.
• Drive hiring, talent development, and team structure optimization.

Data Infrastructure & Governance

• Collaborate with Data Engineering and MLOps teams to ensure robust pipelines, feature stores, and model deployment workflows.
• Improve data quality, observability, and governance standards.

Qualifications:

Education

Bachelor’s or Master’s degree in Data Science, Computer Science, Engineering, Math, or a related field (PhD is a plus).

Experience

• 5+ years of experience in Data Science, Machine Learning, or Applied Analytics.
• 3+ years in a DS leadership role (Lead DS, Head of DS, Director of DS, or similar).
• Demonstrated experience building and leading Data Science teams.
• Proven track record of delivering DS/ML solutions with real business impact.

Technical Skills

• Strong understanding of ML algorithms, experimentation, predictive modeling, and statistical analysis.
• Hands-on experience with Python, ML frameworks (TensorFlow, PyTorch, Scikit-learn), and analytics tooling.
• Solid understanding of data pipelines, big data technologies, and collaboration with Data Engineering teams.
• Experience with AdTech, attribution, auction mechanics, or optimization algorithms is a strong plus.

Leadership & Soft Skills

• Excellent stakeholder management and communication skills.
• Ability to translate technical concepts into business language.
• Strong decision-making and prioritization abilities.
• Passion for mentoring, coaching, and building high-performing teams.

What We Offer:

• Opportunity to build and lead the Data Science function of a global product company.
• Direct influence on product roadmap and business outcomes.
• Collaborative and international team environment.
• Competitive compensation package and growth opportunities.
• A chance to shape the future of mobile app monetization.

Senior Data Scientist — Verify V2 Data Products, Insights & Monetization

Mission

Build the quantitative foundation that proves and amplifies Verify v2's value—transforming verification telemetry into a reliable, customer-facing data infrastructure that demonstrates measurable ROI, optimizes channel economics, and lays the groundwork for an autonomous identity and verification platform.

You'll own the end-to-end data pipeline from raw events to customer-visible metrics that answer the question every customer asks: "What is this product actually worth to my business?"

What You'll Own

1. Customer Value Infrastructure (Prove ROI at Every Level)

Build the metrics that quantify customer-specific business impact:

• Design and maintain a real-time Customer ROI Engine calculating cost-per-successful-verification, fraud savings, conversion lift, and time-to-value by customer, segment, and use case
• Create customer-facing Value Dashboards showing verification success rates vs. industry benchmarks, cost efficiency trends, and projected savings
• Develop attribution models connecting verification outcomes to downstream business metrics (account activations, transaction completion, fraud prevented)

Establish pricing intelligence at the customer level:

• Build granular unit economics visibility: cost-to-serve, margin contribution, and channel mix efficiency per customer
• Model willingness-to-pay signals and usage patterns to inform tiered pricing and custom packaging
• Quantify the revenue impact of workflow configurations (Silent Auth-first vs. SMS fallback economics)

2. Channel Performance & Optimization (Make Every Verification Smarter)

Create a single source of truth for channel economics:

• Unified performance metrics across SMS, Voice, Email, WhatsApp, and Silent Authentication: deliverability, latency, conversion rate, cost-per-success, and failure taxonomy
• Country × carrier × channel performance matrices with confidence intervals and anomaly flags
• Real-time channel health monitoring with automated alerting for degradation

Build the intelligence layer for workflow optimization:

• Predictive models for optimal channel routing (next-best-channel given geography, time, customer segment, historical performance)
• Fallback effectiveness analysis: quantify conversion recovery and cost trade-offs for each fallback path
• Silent Authentication signal analysis: success/rejection drivers, speed benchmarks, and UX impact measurement

3. Product Data Platform (Foundation for Autonomy)

Design data architecture that enables autonomous decision-making:

• Define the canonical event schema and taxonomy for all verification touchpoints (API calls, webhook events, workflow steps, outcomes)
• Build certified, versioned datasets powering self-serve analytics, ML models, and customer-facing products
• Implement data quality infrastructure: lineage tracking, anomaly detection, freshness SLAs, and automated reconciliation

Ship ML/analytics products that move toward autonomous verification:

• Conversion propensity models: predict verification success probability in real-time to optimize routing
• Fraud & abuse detection: anomaly scoring for traffic pumping, IRSF patterns, and bot behavior—with automated response recommendations
• Time-to-verify prediction: forecast completion time to enable SLA commitments and dynamic timeout tuning
• Customer segmentation: behavioral and commercial clustering for personalized workflows and pricing

4. Monetization (Turn Data into Revenue)

Develop data products that customers will pay for:

• Verification Intelligence Suite: premium analytics, industry benchmarks, and deliverability diagnostics
• Workflow Optimizer: ML-driven recommendations for channel sequencing, timeout configuration, and fallback strategies by geography and vertical
• Fraud Protection Package: risk scoring, pumping detection, and abuse pattern alerts with quantified savings

Define commercial success:

• Package entitlements, usage thresholds, and upgrade triggers
• Track attach rates, retention lift, and expansion revenue attributable to data products
• Build the business case for each offering with clear ROI narratives

Key Responsibilities

• Own the customer value narrative: Build and maintain the infrastructure that lets every customer (and our sales team) articulate Verify's ROI in dollars and percentages
• Ship production ML systems: From feature engineering through deployment, monitoring, and iteration
• Create reliable, self-serve data products: Dashboards, APIs, and datasets that scale without manual intervention
• Drive pricing and packaging decisions: Provide the quantitative foundation for how we charge and what we bundle
• Partner across the organization: Work with Product, Engineering, Finance, Sales, and Customer Success to embed data into every decision
• Report to leadership: Own KPI narratives on margin drivers, growth levers, and competitive positioning

Success Measures

What "Great" Looks Like

Core Data Science

• Experimentation design and causal inference (A/B testing, CUPED, uplift modeling, instrumental variables)
• Predictive modeling: classification, survival analysis, time series, real-time scoring
• Anomaly detection with adversarial thinking (fraud patterns, traffic manipulation, abuse signals)
• Customer analytics: segmentation, LTV modeling, churn prediction, cohort economics

Data Engineering Fluency

• Strong SQL; Python (pandas, scikit-learn, PySpark); comfortable shipping production code
• Event-driven architecture: streaming pipelines and real-time analysis and adaptation (Apache Flink), webhook processing, idempotency, late-arrival handling
• Data modeling: star schemas, semantic layers, data contracts, metric certification
• MLOps: feature stores, model monitoring, CI/CD for analytics, orchestration (Airflow/Dagster)

Product & Commercial Analytics

• Pricing analytics: unit economics, willingness-to-pay estimation, margin optimization
• Funnel analysis for multi-step, multi-channel workflows
• Dashboard design and narrative clarity (Looker, Tableau, dbt metrics layer)
• Packaging and monetization strategy for data products

Domain Expertise (Highly Valued)

• CPaaS, verification, or 2FA: OTP mechanics, deliverability constraints, carrier relationships
• Silent Authentication: network-based verification, success/rejection drivers, integration patterns
• Fraud and risk: traffic pumping, IRSF, bot detection, abuse economics
• Privacy and compliance: GDPR/CCPA, data minimization, audit requirements, customer-facing data controls

Background

• 5–8+ years in data science/analytics, with ≥2 years building and shipping data products
• Track record of translating ambiguous business questions into measurable outcomes
• Experience in B2B SaaS, identity/auth, fintech, messaging/telecom, or fraud analytics preferred
• Demonstrated ability to influence product and pricing decisions with data

Why This Role Matters

Verification is shifting from a cost center to a strategic differentiator. The data infrastructure you build will:

1. Prove value — Give every customer undeniable evidence of ROI
2. Optimize economics — Make every verification faster, cheaper, and more reliable
3. Enable autonomy — Lay the foundation for a platform that routes, optimizes, and protects without human intervention

You'll shape how Vonage—and our customers—think about identity verification as a measurable, optimizable, intelligent system.

#LI-WW1

As a Staff Machine Learning Engineer in our Applied ML & Research team, you'll drive the development of cutting-edge machine learning solutions that power critical features across our online gaming platforms. Your work will directly impact platform security, user experience, and large-scale data-driven decision-making for hundreds of thousands of users daily.

This role blends hands-on technical work with strategic thinking. You’ll lead by example, contribute high-quality code, and help shape the ML roadmap in the organization through cross-functional collaboration.

What you’ll you be doing:

• Identify high-impact ML opportunities and influence stakeholders to prioritize and support these initiatives.
• Design and develop scalable machine learning models — including classifiers, regressors, and rule-based systems — to solve real-world problems.
• Own the full ML lifecycle: from data exploration and feature engineering to model training, evaluation, and deployment.
• Translate complex technical concepts into clear insights for both technical and non-technical stakeholders.
• Set and guide technical direction across ML projects, ensuring technical best practices as well as alignment with business goals.
• Mentor junior engineers and foster a culture of knowledge sharing and continuous improvement.

We're looking for someone with:

• Master’s degree (or equivalent) in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field.
• 7+ years of industry experience building and deploying ML models at scale.
• Proven ability to lead cross-functional technical initiatives and influence engineering strategy.
• Proficiency in Python (with libraries like PyTorch, XGBoost, Scikit-learn) and SQL.
• Strong experience with machine learning pipelines and orchestration tools such as Airflow, SageMaker Pipelines, or similar.
• Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies.
• A track record of shipping production-level ML products and maintaining high code quality.
• Excellent problem-solving skills and ability to scope and disambiguate complex ML projects into clear, achievable milestones.

Bonus points for:

• Familiarity with ML tooling such as MLflow, ZenML, or Metaflow.
• Hands-on experience with AWS services (e.g., EC2, EKS, CloudFormation, Cognito).
• Exposure to streaming data platforms like Kafka.
• Contributions to open-source ML projects or publications in ML conferences.

As a Staff Machine Learning Engineer in our Applied ML & Research team, you'll drive the development of cutting-edge machine learning solutions that power critical features across our online gaming platforms. Your work will directly impact platform security, user experience, and large-scale data-driven decision-making for hundreds of thousands of users daily.

This role blends hands-on technical work with strategic thinking. You’ll lead by example, contribute high-quality code, and help shape the ML roadmap in the organization through cross-functional collaboration.

What you’ll you be doing:

• Identify high-impact ML opportunities and influence stakeholders to prioritize and support these initiatives.
• Design and develop scalable machine learning models — including classifiers, regressors, and rule-based systems — to solve real-world problems.
• Own the full ML lifecycle: from data exploration and feature engineering to model training, evaluation, and deployment.
• Translate complex technical concepts into clear insights for both technical and non-technical stakeholders.
• Set and guide technical direction across ML projects, ensuring technical best practices as well as alignment with business goals.
• Mentor junior engineers and foster a culture of knowledge sharing and continuous improvement.

We're looking for someone with:

• Master’s degree (or equivalent) in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field.
• 7+ years of industry experience building and deploying ML models at scale.
• Proven ability to lead cross-functional technical initiatives and influence engineering strategy.
• Proficiency in Python (with libraries like PyTorch, XGBoost, Scikit-learn) and SQL.
• Strong experience with machine learning pipelines and orchestration tools such as Airflow, SageMaker Pipelines, or similar.
• Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies.
• A track record of shipping production-level ML products and maintaining high code quality.
• Excellent problem-solving skills and ability to scope and disambiguate complex ML projects into clear, achievable milestones.

Bonus points for:

• Familiarity with ML tooling such as MLflow, ZenML, or Metaflow.
• Hands-on experience with AWS services (e.g., EC2, EKS, CloudFormation, Cognito).
• Exposure to streaming data platforms like Kafka.
• Contributions to open-source ML projects or publications in ML conferences.

As a Staff Machine Learning Engineer in our Applied ML & Research team, you'll drive the development of cutting-edge machine learning solutions that power critical features across our online gaming platforms. Your work will directly impact platform security, user experience, and large-scale data-driven decision-making for hundreds of thousands of users daily.

This role blends hands-on technical work with strategic thinking. You’ll lead by example, contribute high-quality code, and help shape the ML roadmap in the organization through cross-functional collaboration.

What you’ll you be doing:

• Identify high-impact ML opportunities and influence stakeholders to prioritize and support these initiatives.
• Design and develop scalable machine learning models — including classifiers, regressors, and rule-based systems — to solve real-world problems.
• Own the full ML lifecycle: from data exploration and feature engineering to model training, evaluation, and deployment.
• Translate complex technical concepts into clear insights for both technical and non-technical stakeholders.
• Set and guide technical direction across ML projects, ensuring technical best practices as well as alignment with business goals.
• Mentor junior engineers and foster a culture of knowledge sharing and continuous improvement.

We're looking for someone with:

• Master’s degree (or equivalent) in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field.
• 7+ years of industry experience building and deploying ML models at scale.
• Proven ability to lead cross-functional technical initiatives and influence engineering strategy.
• Proficiency in Python (with libraries like PyTorch, XGBoost, Scikit-learn) and SQL.
• Strong experience with machine learning pipelines and orchestration tools such as Airflow, SageMaker Pipelines, or similar.
• Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies.
• A track record of shipping production-level ML products and maintaining high code quality.
• Excellent problem-solving skills and ability to scope and disambiguate complex ML projects into clear, achievable milestones.

Bonus points for:

• Familiarity with ML tooling such as MLflow, ZenML, or Metaflow.
• Hands-on experience with AWS services (e.g., EC2, EKS, CloudFormation, Cognito).
• Exposure to streaming data platforms like Kafka.
• Contributions to open-source ML projects or publications in ML conferences.

As a Staff Machine Learning Engineer in our Applied ML & Research team, you'll drive the development of cutting-edge machine learning solutions that power critical features across our online gaming platforms. Your work will directly impact platform security, user experience, and large-scale data-driven decision-making for hundreds of thousands of users daily.

This role blends hands-on technical work with strategic thinking. You’ll lead by example, contribute high-quality code, and help shape the ML roadmap in the organization through cross-functional collaboration.

What you’ll you be doing:

• Identify high-impact ML opportunities and influence stakeholders to prioritize and support these initiatives.
• Design and develop scalable machine learning models — including classifiers, regressors, and rule-based systems — to solve real-world problems.
• Own the full ML lifecycle: from data exploration and feature engineering to model training, evaluation, and deployment.
• Translate complex technical concepts into clear insights for both technical and non-technical stakeholders.
• Set and guide technical direction across ML projects, ensuring technical best practices as well as alignment with business goals.
• Mentor junior engineers and foster a culture of knowledge sharing and continuous improvement.

We're looking for someone with:

• Master’s degree (or equivalent) in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field.
• 7+ years of industry experience building and deploying ML models at scale.
• Proven ability to lead cross-functional technical initiatives and influence engineering strategy.
• Proficiency in Python (with libraries like PyTorch, XGBoost, Scikit-learn) and SQL.
• Strong experience with machine learning pipelines and orchestration tools such as Airflow, SageMaker Pipelines, or similar.
• Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies.
• A track record of shipping production-level ML products and maintaining high code quality.
• Excellent problem-solving skills and ability to scope and disambiguate complex ML projects into clear, achievable milestones.

Bonus points for:

• Familiarity with ML tooling such as MLflow, ZenML, or Metaflow.
• Hands-on experience with AWS services (e.g., EC2, EKS, CloudFormation, Cognito).
• Exposure to streaming data platforms like Kafka.
• Contributions to open-source ML projects or publications in ML conferences.

As a Staff Machine Learning Engineer in our Applied ML & Research team, you'll drive the development of cutting-edge machine learning solutions that power critical features across our online gaming platforms. Your work will directly impact platform security, user experience, and large-scale data-driven decision-making for hundreds of thousands of users daily.

This role blends hands-on technical work with strategic thinking. You’ll lead by example, contribute high-quality code, and help shape the ML roadmap in the organization through cross-functional collaboration.

What you’ll you be doing:

• Identify high-impact ML opportunities and influence stakeholders to prioritize and support these initiatives.
• Design and develop scalable machine learning models — including classifiers, regressors, and rule-based systems — to solve real-world problems.
• Own the full ML lifecycle: from data exploration and feature engineering to model training, evaluation, and deployment.
• Translate complex technical concepts into clear insights for both technical and non-technical stakeholders.
• Set and guide technical direction across ML projects, ensuring technical best practices as well as alignment with business goals.
• Mentor junior engineers and foster a culture of knowledge sharing and continuous improvement.

We're looking for someone with:

• Master’s degree (or equivalent) in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field.
• 7+ years of industry experience building and deploying ML models at scale.
• Proven ability to lead cross-functional technical initiatives and influence engineering strategy.
• Proficiency in Python (with libraries like PyTorch, XGBoost, Scikit-learn) and SQL.
• Strong experience with machine learning pipelines and orchestration tools such as Airflow, SageMaker Pipelines, or similar.
• Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies.
• A track record of shipping production-level ML products and maintaining high code quality.
• Excellent problem-solving skills and ability to scope and disambiguate complex ML projects into clear, achievable milestones.

Bonus points for:

• Familiarity with ML tooling such as MLflow, ZenML, or Metaflow.
• Hands-on experience with AWS services (e.g., EC2, EKS, CloudFormation, Cognito).
• Exposure to streaming data platforms like Kafka.
• Contributions to open-source ML projects or publications in ML conferences.