(junior) fullstack engineer (m/f/d) for a new product

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decision scientist, revenue, ads Jobs in Berlin

decision scientist, revenue, ads

decision scientist revenue ads

Vinted

<div>
 
 Brief Info About Vinted
 
 
 
 Our mission is to make second-hand the first choice, and we're looking for people who want to help us get there. Every day, we work together to help our members buy and sell pre-loved clothing and lifestyle items, giving each piece a second life &ndash; or even a third.
 
 
 The Vinted Group is made up of three business units that support this mission:
 
 
 
 Vinted Marketplace
 
 is Europe&rsquo;s leading platform for second-hand fashion and a go-to destination for all kinds of pre-loved items, with a growing range of categories. Our platform connects millions of members across 20+ markets, helping great items find a new life.
 
 
 
 Vinted Go
 
 enhances the shipping experience with a vast network of over 500,000 pick-up and drop-off points, partnering with more than 60 carriers across Europe, with added services like item verification for peace of mind on high-value pieces.
 
 
 
 Vinted Pay
 
 is the newest part of the Vinted Group, dedicated to bringing secure, reliable payments to buyers and sellers across Europe. Seamlessly integrated into the Vinted app, it helps keep every transaction safe, efficient, and easy for our members.
 
 
 Founded in 2008 in Lithuania, Vinted began as a way for friends to find new homes for clothes they no longer needed. In 2019, we became Lithuania's first unicorn! Today, our headquarters remain in Vilnius, and we've grown with offices across Europe, supported by a team of over 2,000 people.
 
 
 
 Information About The Position
 
 
 
 Vinted&rsquo;s Revenue domain is growing &mdash; Ads business is on the mission to develop an advertising ecosystem within Vinted and we&rsquo;re just getting started. We are a cross-functional team of Designers, Product Managers, Engineering and Data professionals. We also work closely with Ads Operations and Ads Sales business units. We&rsquo;re looking for a Decision Scientist to join Ads to help us make the most of our real estate and evolve toward a high‑performance, privacy‑respectful, in‑house advertising ecosystem over time. Think: an ad of an external partner can generate euros directly but we may well advertise our own Marketplace services or let the user go undisturbed in their Vinted path. If you love shaping greenfield problems, developing user experience and turning data into decisions that bring impact, this role is for you.
 
 
 
 In this position, you&rsquo;ll
 
 
 
 <ul>
 <li>
 Drive domain objectives: Balance performance and user experience within the marketplace for the most optimal long-term outcomes for advertisers and Vinted members.
 </li>
 <li>
 Lead data-driven decision-making: Partner with your team and stakeholders at Vinted, to identify strategic opportunities and provide data-informed recommendations, as well as answer critical business questions.
 </li>
 <li>
 Ensure collaboration and alignment: Partner closely with Data Scientists, Ads Engineering, Ad Operations, Product, and Revenue leadership teams to translate business goals into robust data and model choices. Communicate trade-offs clearly and early.
 </li>
 <li>
 Unlock impact with data: Leverage internal behavioural signals to improve impression performance while respecting user well-being. Turn insights into actionable policies that scale across campaigns and surfaces.
 </li>
 <li>
 Leverage experimentation: Test and analyse new ads types and placements to validate their value and understand their business impact, using statistical methods and visualisation tools. Lead the culture of iterative development and AB testing.
 </li>
 <li>
 Raise the bar on quality: Establish clear metrics for success (delivery health, incremental revenue, ad harm), instrument reliable measurements through experimentation.
 </li>
 <li>
 Enable stakeholders: Create self-service tools for your product team and business stakeholders to independently leverage data for business insights.
 </li>
 <li>
 Build the future: Contribute to the long-term vision of a Vinted Ads Network. Ensure that placements for ads are located in optimal spaces in the app, considering Advertiser performance and user experience.
 </li>
 <li>
 Continuously improve: Stay current on optimisation, experimentation, and ads tech best practices &mdash; and bring those ideas into our day-to-day.
 
 
 </li>
 </ul>
 
 About You
 
 
 
 <ul>
 <li>
 Experience in a Decision Science, Data Analytics role or equivalent experience
 </li>
 <li>
 Experienced with statistical methods, such as A/B testing, regression analysis, and other inferential techniques
 </li>
 <li>
 Highly results-oriented, comfortable with iterative processes and prioritising the most impactful work
 </li>
 <li>
 A conscious team player who understands when their work touches that of other team members and proactively aligns with them
 </li>
 <li>
 Good analytical thinker and problem-solver, with the ability to balance depth of analysis with business impact
 </li>
 <li>
 Experienced with SQL and Python
 </li>
 <li>
 Experienced with BI tools (e.g., Looker, Tableau, Power BI)
 </li>
 <li>
 Strong communicator who can convincingly present results to both technical and non-technical audiences
 </li>
 <li>
 Fluent in English, both written and spoken
 </li>
 <li>
 Bonus: experience with AdTech product development (double bonus for Ads Publishing analytics knowledge)
 
 
 </li>
 </ul>
 
 Work perks
 
 
 
 <ul>
 <li>
 The opportunity to benefit from our share options programme
 </li>
 <li>
 30 days of paid annual leave
 </li>
 <li>
 Newest MacBook models
 </li>
 <li>
 Digital mental and emotional health support and Employee Assistant Program (EAP)
 </li>
 <li>
 Home office support: we provide IT workstation equipment and a personal budget of up to &euro;540 for home workplace furniture
 </li>
 <li>
 Lunch benefit per your workday
 </li>
 <li>
 Frequent team-building events
 </li>
 <li>
 A personal monthly budget for shopping on Vinted
 </li>
 <li>
 Access to a discounted gym membership plan
 </li>
 <li>
 Pension Plan with Vinted matching 150% of your chosen contribution
 </li>
 <li>
 Supplemental Private Health Insurance
 </li>
 <li>
 Life and Disability insurance
 </li>
 <li>
 A subsidised Deutschlandticket for your commute to the office by public transport
 </li>
 <li>
 The opportunity to spend up to 90 days per year - 21 of which can be spent working outside of the EU - on workation
 </li>
 <li>
 A dog-friendly office
 
 
 </li>
 </ul>
 
 Working at Vinted
 
 
 
 
 Individual Learning Budget
 
 
 
 We invest in your professional growth! As part of our commitment to continuous learning, we offer an annual learning budget to support your personal and career development through courses, certifications, workshops and more.
 
 
 
 Hybrid Work
 
 
 
 We&rsquo;ve adopted a hybrid workplace model where 2 days in the office are recommended but not enforced. It&rsquo;s up to you and your team to decide on the exact days you&rsquo;ll spend working together in person.
 
 
 
 Equal Opportunity
 
 
 
 The Vinted Group is committed to building an inclusive workplace where people from all walks of life feel a sense of belonging. We welcome applications from people of all backgrounds, identities and life experiences. At Vinted, all applicants are treated fairly without regard to their race, age, religion or belief, sex, national origin, citizenship, gender identity, sexual orientation, disability, or any other protected characteristic.
 
 
 The annual gross salary range for this position is:
 
 
 &euro;61.200&mdash;&euro;100.100 EUR
</div>

Decision Scientist, Revenue, Ads

adjoe

<div>adjoe builds the technologies behind mobile app growth and monetization, challenging the status quo of adtech by redefining how apps acquire users and generate revenue. Our two products, Playtime Arcade and adjoe Ads, sit at opposite ends of the mobile advertising spectrum: rewarded engagement and programmatic in-app advertising. Together they run on 13% of the world's smartphones, connecting advertisers, publishers, and hundreds of millions of users, with one goal: making mobile advertising work better for everyone in the ecosystem.
Next-Gen Machine Intelligence for Scalable Discovery &amp; Engagement
The Data Science Research team builds foundational ML representations and advanced AI capabilities that enhance both Playtime and adjoe Ads. Operating as a horizontal deep-tech layer, the team leverages advanced AI and deep learning approaches&mdash;specifically generative approaches &mdash;to deliver critical systems such as high-dimensional user embeddings, general content understanding and sequential recommendation. These frameworks scale adjoe's products beyond standard industry limitations, utilizing behavioral and transactional data from over 770 million users.
The team operates at the intersection of bleeding-edge R&amp;D and high-scale production engineering, acting as the company&rsquo;s internal science bar raiser and primary consulting layer for complex ML bottlenecks. The stack is optimized for deep learning and heavy data throughput: PyTorch and [Ray/Hugging Face] for training and fine-tuning foundation models, Trino and Athena for querying massive user-behavior data lakes, and dedicated GPU infrastructure for heavy workloads. The full lifecycle of these AI capabilities is owned by the team&mdash;from academic paper translation and offline prototyping to deploying core algorithmic frameworks built to sustain high-throughput, realtime production environments.
Your Mission &amp; Who We Are Looking For:<ul><li>
PhD or equivalent research depth, with a track record of technical mentorship. PhD in CS, Statistics, Math, or Physics. Publications in SIGIR, KDD, NeurIPS, or ICLR, and 5+ years building large-scale recommender systems in AdTech, e-commerce, or social. You've owned architectural bets and had accountability for outcomes.</li><li>
You set the research direction. You identify the highest-leverage problems at the intersection of generative AI and recommendation, define the multi-quarter research agenda, and align engineering and product leadership. That means owning how Generative Retrieval, Deep Ranking, and Re-ranking evolve across a stack built on 770 million users' behavioral data.</li><li>
Deep expertise in PyTorch and large-scale model optimization. Hands-on with high-concurrency optimization, quantization, and distillation &mdash; getting large generative models to run under extreme production constraints, not just in research environments.</li><li>
You are the company's deepest resource on generative recommendation. You translate SOTA research into systems adjoe can ship, review architectural decisions across teams, and raise the ML quality bar company-wide. When there's a hard bottleneck, you're the first call.</li><li>
You grow the teams around you. You mentor senior and mid-level scientists, lead architectural debates, and drive long-horizon investments without needing a roadmap handed to you.</li></ul>
We welcome applications from talent worldwide and provide relocation support to Hamburg, Germany for those ready to join our team.
What&rsquo;s in It for You?
At adjoe, you&rsquo;re not here to just close JIRA tickets, you&rsquo;re helping build the infrastructure behind one of the most impactful platforms in adtech. The systems you work on will reach hundreds of millions of users and power billions of decisions every day.<ul><li>
Go Big. Own projects with impact on 770M users and push adtech boundaries.</li><li>
Move Fast. Ship solutions multiple times a day, learn from results, and keep momentum.</li><li>
Be Direct. Solve problems openly and collaborate across teams.</li><li>
Thrive Together. Grow with a diverse, global team of people from over 40 different countries that learn from each other.</li><li>
Have Fun. Celebrate wins, enjoy daily victories, and bring your energy.</li></ul>
We welcome applications from people who will contribute to the diversity of our company.</div>

Staff ML Research Scientist (m/f/d)

Audible

<div>
 
 Description
 
 
 
 At Audible, we believe stories have the power to transform lives. It&rsquo;s why we work with some of the world&rsquo;s leading creators to produce and share audio storytelling with our millions of global listeners. We are dreamers and inventors who come from a wide range of backgrounds and experiences to empower and inspire each other. Imagine your future with us.
 
 
 
 About This Role
 
 
 
 As an Applied Scientist, you will solve large complex real-world problems at scale, draw inspiration from the latest science and technology to empower undefined/untapped business use cases, delve into customer requirements, collaborate with tech and product teams on design, and create production-ready models that span various domains, including Machine Learning (ML), Artificial Intelligence (AI) and Generative AI, Natural Language Processing (NLP), Reinforcement Learning (RL), real-time and distributed systems.
 
 
 
 About You
 
 
 
 Your work will focus on inventing or adapting scientific approaches, models, and algorithms driven by customer needs at the project level. You will develop components and/or end-to-end solutions that are deployed into production or directly support production systems, delivering consistently high-quality work that meets both scientific and engineering best practices. You will develop reusable science components and services that resolve architecture deficiencies and customers&rsquo; pain points, while making technical trade-offs for long-term/short- term. You will work semi-autonomously to deliver solutions, contribute to research papers at peer-reviewed venues when appropriate, and document your work thoroughly to enable others to understand and reproduce it. Your decision-making will consistently incorporate robust, data-driven business and technical judgment. You will collaborate with other scientists to raise the bar of both scientific and engineering complexity for the team and to foster valuable scientific partnership opportunities to help/guide science decisions. We work in a highly collaborative, fast-paced environment where scientists, engineers, and product managers work to test and build scalable foundational capabilities, as well as customer facing experiences. You will have the opportunity to innovate and think big within your projects scope, implement optimization services and algorithms, and influence the experiences of millions of customers. We are looking for a results-oriented Applied Scientist with deep knowledge in ML, NLP, Deep Learning, GenAI, and/or large-scale distributed computation.
 
 
 As an Applied Scientist, you will...
 
 
 <ul>
 <li>
 Understand use cases across the business and adopt/extend/design/invent solutions/models that are scalable, efficient, and automated for difficult problems that are not well defined
 </li>
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 Work closely with fellow scientists and software engineers (at Audible and Amazon) to build and productionize models, deliver novel and highly impactful features
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 Review models of peers for the purpose of reducing and managing risk to the business, while improving customer experience
 </li>
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 Design, develop, and deploy modeling techniques and solutions for Content Understanding, Recommendations, GenAI-based product features, by employing a wide range of methodologies, working from simple to complex
 </li>
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 Contribute to initiatives that employ the most recent advances in ML/AI in a fast-paced, experimental environment
 </li>
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 Push the boundary of innovation
 
 
 </li>
 </ul>
 
 About Audible
 
 
 
 Audible is the leading producer and provider of audio storytelling. We spark listeners&rsquo; imaginations, offering immersive, cinematic experiences full of inspiration and insight to enrich our customers daily lives. We are a global company with an entrepreneurial spirit. We are dreamers and inventors who are passionate about the positive impact Audible can make for our customers and our neighbors. This spirit courses throughout Audible, supporting a culture of creativity and inclusion built on our People Principles and our mission to build more equitable communities in the cities we call home.
 
 
 
 Basic Qualifications
 
 
 
 <ul>
 <li>
 3+ years of building models for business application experience
 </li>
 <li>
 PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
 </li>
 <li>
 Experience in patents or publications at top-tier peer-reviewed conferences or journals
 </li>
 <li>
 Experience programming in Java, C++, Python or related language
 </li>
 <li>
 Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
 </li>
 <li>
 MSc + 5ys of relevant experience, or PhD +1 year in one of the following disciplines: Machine Learning, Computer Science, Computer Engineering, Data Science, Applied Math, or a related quantitative field
 </li>
 <li>
 3+ years of experience in Deep Learning, Natural Language
 </li>
 <li>
 Processing/Understanding, GenAI and/or Reinforcement Learning
 </li>
 <li>
 Proficiency in Python, SQL, and other scripting languages
 </li>
 <li>
 Experience employing and innovating with LLMs/GenAI to solve complex problems
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Experience using Unix/Linux
 </li>
 <li>
 Experience in professional software development
 </li>
 <li>
 Experience with building Recommendation Systems
 </li>
 <li>
 Machine Learning Pipeline orchestration with AWS (SageMaker, Batch, Lambda, Step Functions) or similar cloud-platforms
 
 
 </li>
 </ul>
 Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.
 
 
 m/w/d
 
 
 Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner.
 
 
 
 
 Company
 
 - Audible GmbH - B38
 
 
 Job ID: A10450357
</div>

Applied Scientist

Billie

<div>We are Billie, the leading provider of Buy Now, Pay Later (BNPL) payment methods for businesses, offering B2B companies innovative digital payment services and modern checkout solutions. We are to create a new standard for business payments and have made it our mission to simplify the purchasing experience for all businesses making it a tool for growth. Our solutions are based on proprietary, machine-learning-supported risk models, fully digitized processes and a highly scalable tech platform. This makes us a deep-tech company building financial products, not the other way around. We love building simple and elegant solutions and we strive for automation and scalability.
As part of Decision Science, you will work on the models that decide, in milliseconds, whether a transaction is trustworthy. Your work directly shapes how much fraud we stop, how many good customers we approve, and how much risk the business carries.<div></div> 
About the role:
As a Fraud Data Scientist, you will be a core technical contributor within Billie's Decision Science group. You will design and build robust, scalable machine learning solutions that prevent fraud, with a direct and measurable impact on Billie's bottom line. You will own the end-to-end modeling lifecycle: defining the analytical approach, testing hypotheses, and deploying models that capture complex debtor behavior and emerging fraud patterns.<div></div> 
In more detail, you will:<ul><li>
Design and ship anti-fraud models, taking ownership of project priorities and delivering production-ready solutions.</li><li>
Model debtor behavioral patterns, identify risk factors, and optimize the logic of Billie's real-time decision engine using quantitative analysis, data mining, and advanced ML.</li><li>
Balance precision and recall under severe class imbalance, explicitly weighing the cost of false positives (customer friction) against missed fraud (financial loss).</li><li>
Monitor deployed models for drift and adversarial adaptation, and retrain or recalibrate as fraud patterns shift.</li><li>
Collaborate with data and software engineers, analysts, and product managers to improve decision logic, integrate new data sources, and extend system functionality.</li><li>
Own the deployment and operationalization of ML services within real-time latency constraints, working with Engineering on infrastructure requirements such as containerization and event-driven architectures.</li><li>
Share knowledge across the team and contribute to strong experimentation and coding practices.</li><li>
Turn technical findings into clear, actionable recommendations through effective data storytelling for both technical and non-technical stakeholders.</li></ul>
What you bring to the team:<div></div> 
Must have:<ul><li>
3-5+ years in a quantitative or machine learning role, ideally in fintech or another high-transaction environment. Direct experience in fraud prevention or risk modeling is strongly preferred.</li><li>
Proven advanced proficiency in Python (e.g. pandas, scikit-learn, xgboost) and SQL (Snowflake, Postgres, or MySQL).</li><li>
Deep expertise in classification models (classical and deep learning), anomaly detection, and graph-based methods (e.g., graph neural networks, entity-link analysis).</li><li>
Hands-on experience productionizing ML services, with a strong grasp of modern MLOps concepts such as containerization (Docker/Kubernetes) and event-driven architectures.</li><li>
Proven ability to manage stakeholders across technical and non-technical functions, aligning technical roadmaps with business priorities.</li><li>
Sharp problem-solving skills, with the ability to translate complex business challenges into clean, efficient, and scalable technical requirements.</li><li>
Strong communication skills, with a track record of using data to influence strategy and drive cross-functional engagement.</li></ul>
Nice to have:<ul><li>
Experience with ML orchestration frameworks such as Metaflow, Apache Flink, or similar MLOps tooling.</li><li>
Experience implementing LLM-based workflows (e.g., agentic pipelines, retrieval-augmented generation, or LLM-assisted feature extraction), particularly applied to fraud detection or risk signals.</li></ul>
What We Offer:<ul><li>
Challenging and impactful work that drives personal and professional growth</li><li>
One of the best Virtual Shares Incentive Programs in the market, so that everyone at Billie is invested in our success</li><li>
Flexible work hours and trust in your ability to deliver, empowering you to take control of your work-life balance</li><li>
A hybrid working approach that allows you to work from home for up to 3 days per week</li><li>
Enjoy 30 days vacation per year, sabbatical opportunities, and extra child sickness leave for parents.</li><li>
Our &ldquo;Catch a Ride with Billie&rdquo; program that enables discounted access to Berlin Public Transport (BVG), Deutschland-Ticket, OR JobRad</li><li>
A yearly development budget to broaden your skill set and horizons</li><li>
Free German group classes</li><li>
An English-speaking, multicultural team with more than 40 nationalities</li><li>
Building meaningful connections with your colleagues through company and team events, interest groups, the Billie run club, game nights, and more, powered by our Formula Fun Team!</li></ul>
Billie is an equal opportunity employer and we do not discriminate on the basis of race, color, religion, sexual orientation, gender identity or expression, national origin, age, disability, or any other protected characteristic. We are committed to creating an inclusive environment where everyone feels they belong. All qualified applicants are welcome and we especially encourage you to apply, even if you don't check every box in the job description.
For information about data processing see our &quot;Recruiting Privacy Policy and further information&quot;: https://www.billie.io/en/candidate-information</div>

Fraud Data Scientist

Zalando

<div><div>Ort</div><div>
Germany - Berlin</div><div>
Vertrag</div><div>
Full time</div><div>
Job-Kategorie</div><div>
Applied Science &amp; Research</div></div>
 <div><div><h1 class="jobSectionHeader">Applied Scientist (all genders) - B2B Data Science and Algorithms</h1>
The ZEOS department is responsible for all partner-facing Zalando Logistics Solutions. We provide a holistic approach to delivering the fulfillment solutions that meet our partner&rsquo;s needs by unifying these services under a single umbrella. We aim to provide our partners with a profitable fulfilment experience, and we see that to do this, Machine Learning, Operations Research and Data-driven solutions will play a pivotal role.
We are seeking an Applied Scientist who is fueled by the desire to build innovative and impactful ML/Optimization systems for our B2B logistics partners. You will join an existing team of Applied Scientists, and Machine Learning Engineers and work in a cross-functional setup with Product Managers, Data and Software Engineers.
The team&rsquo;s focus is helping our B2B partners improve inventory health and order fulfilment efficiency. You will be building various ML/DL forecasting models (demand, returns, lead-times), stochastic inventory optimization solutions, recommendation services and emerging Agentic AI systems that generate these key insights for our partners and enable them to make data-driven decisions about their article assortment and inventory. You will play a key role in a cross-functional team!<h2 class="jobSectionHeader">
WHY YOU SHOULD BE INTERESTED&hellip;</h2><ul><li>
Shape the Product from Day One: You won't be a &quot;model factory&quot; stuck in a silo! You will be a core scientific partner, working directly with product and user research to define the problem, not just solve it. Your expertise will directly influence the product roadmap and identify new opportunities to create value for our partners.</li></ul><ul><li>
Solve High-Stakes, Complex Scientific Problems: This is your chance to go beyond standard forecasting. You'll be tackling cutting-edge challenges in stochastic inventory optimization, multi-echelon demand forecasting (including returns and lead-times), and building recommender systems for assortment planning. Your work will be at the absolute core of our partners' profitability.</li></ul><ul><li>
Pioneer Agentic AI &amp; Robust Evaluations: As we explore opening up MCP servers to our partners, you will contribute to defining how we measure their performance/success in the user&rsquo;s agentic journey. You will design and implement rigorous Agentic AI evaluation frameworks/metrics (e.g., LLM-as-a-judge, trajectory evaluation, and safety guardrails) to ensure the autonomous systems connecting to the MCPs act reliably and logically on behalf of our B2B partners.</li></ul><ul><li>
End-to-End Ownership: You will have the autonomy to see your ideas through from initial research and prototyping all the way to production. You will define the metrics for success, collaborate with engineers to deploy your models as scalable services, and monitor their real-world impact on partner KPIs.</li></ul><ul><li>
Drive Impact at a multi-merchant scale: Your solutions won't just help one partner. You will be building platform-level services that scale across hundreds of diverse partners/merchants, directly influencing millions of euros in merchandise value and shaping the future of a more sustainable and efficient e-commerce logistics network.</li></ul> 
WE&rsquo;D LOVE TO MEET YOU IF&hellip;<ul><li>
Educational background in a quantitative field - Masters degree or higher preferred.</li><li>
3+ years of hands-on industry experience in an Applied Scientist, Data Scientist, or Research Scientist role, applying scientific methods to solve business problems.</li><li>
Industry demonstrated knowledge and skills in at least one the following areas:<ul><li>
Machine Learning or Deep Learning, particularly applied for time-series forecasting (e.g., LGBM, ARIMA, Prophet, Transformers, Nixtla, Darts,...)</li><li>
Machine Learning Engineering (e.g. service design, batch processing, GPU computing, git, docker, CI/CD, software testing)</li><li>
Operations Research and Optimization, (e.g., stochastic inventory models, linear/integer programming, Monte Carlo simulations, &hellip;)</li><li>
Agentic AI &amp; MCP evaluation frameworks</li></ul></li><li>
Proficiency in SQL and experience working with large-scale datasets.</li><li>
Strong communication skills with the ability to explain complex scientific concepts to product managers and business stakeholders. A collaborative, product-oriented mindset and a desire to see your work create real-world impact.</li><li>
An entrepreneurial mindset, you value a diverse and fast-paced business environment, and hence balance your passion for research with pragmatism to drive actions and create impact for our customers.</li><li>
You have a passion for learning and growing by doing. We are here to help you. One of the preferred values of the team is: &ldquo;High Challenge, High Support&rdquo;!</li><li>
Excellent communication skills! We cherish our open and direct feedback culture in the team!</li></ul>
INCLUSIVE BY DESIGN
At Zalando, our vision is to be the leading pan-European ecosystem for fashion and lifestyle e-commerce - one that is inclusive by design. We only assess candidates based on qualifications, merit, and business needs. We welcome applications from people of all gender identities, sexual orientations, personal expressions, racial identities, ethnicities, religious beliefs, and disability statuses. We only want to know why you're great for this role, so please avoid including your picture, age, and marital status in your CV as well.
We want to provide you with a great candidate experience. Please feel free to inform us of any accommodations you may need, so we can best support and assist you throughout the hiring process.
do.BETTER - our diversity &amp; inclusion strategy: https://jobs.zalando.com/en/our-culture/diversity-and-inclusion
OUR OFFER
Zalando provides a range of benefits, here's an overview of what you can expect. Ask your Talent Acquisition Partner to learn more about what we offer.<ul><li>
Employee shares program</li><li>
40% off fashion and beauty products sold and shipped by Zalando, 30% off Lounge by Zalando, discounts from external partners</li><li>
2 paid volunteering days per year</li><li>
Work from abroad for up to 30 working days a year</li><li>
27 days of vacation a year to start for full-time employees</li><li>
Family services, including counseling and support</li><li>
Health and wellbeing options (including Wellhub, formerly Gympass)</li><li>
Mental health support and coaching available</li><li>
Drive your development through our training platform and biannual peer-to-peer review</li></ul></div><div>
Recruiter
Casimir Udegbunam
casimir.udegbunam@zalando.de</div><div>
 Nach der Pr&uuml;fung werden unsere Recruiter*innen &uuml;ber eine offizielle Zalando E-Mail-Adresse (@zalando.de) Kontakt aufnehmen.
In einigen F&auml;llen arbeiten wir auch mit einer Auswahl von Headhunter*innen und Agenturen zusammen, um bestimmte Positionen zu besetzen. Bitte beachte, dass weder Zalando noch unsere Rekrutierungspartner*innen irgendeine Art von Bezahlung verlangen, um sich f&uuml;r eine Stelle zu bewerben oder an einem Vorstellungsgespr&auml;ch teilzunehmen.</div></div>
 <div></div><div><div><div><h2 class="jobSectionHeader">&Uuml;ber Zalando</h2>
Zalando wurde 2008 in Berlin gegr&uuml;ndet und ist die f&uuml;hrende europ&auml;ische Technologieplattform f&uuml;r Mode und Lifestyle. Wir verbinden 62 Millionen aktive Kund*innen mit mehr als 7.000 Marken in 29 M&auml;rkten. Unser Gesch&auml;ft basiert auf einer einzigartigen, KI-gest&uuml;tzten Daten- und Infrastrukturplattform. F&uuml;r unsere Kund*innen bietet unser Multi-App-Ansatz &ndash; bestehend aus Zalando, ABOUT YOU und Lounge by Zalando &ndash; ein inspirierendes, hochgradig personalisiertes Einkaufserlebnis. F&uuml;r unsere Partner bauen wir das Betriebssystem f&uuml;r den E-Commerce. &Uuml;ber ZEOS, Tradebyte und SCAYLE &ouml;ffnen wir unsere Logistik-, Software- und Servicekapazit&auml;ten f&uuml;r Marken und Einzelh&auml;ndler*innen zur nahtlosen, grenz&uuml;berschreitenden Skalierung ihres Gesch&auml;fts.</div></div></div>

Applied Scientist (all genders) - B2B Data Science and Algorithms

Norwegian Refugee Council

<div>What we are looking for:
We're looking for an experienced Data Scientist to help shape the future of humanitarian action through CLEAR (Crisis Learning, Early Warning and Anticipatory Action) - NRC's open infrastructure designed to transform fragmented crisis data into timely, actionable intelligence. 
CLEAR brings together diverse data sources - including earth observation, conflict data, field reports, and market intelligence - into a shared, open, and federated platform that enables humanitarian teams to anticipate crises and act before they escalate. By closing the gap between insight and action, CLEAR empowers faster, smarter, and more effective humanitarian responses. 
As the Data Scientist, you will play a pivotal role in designing and deploying cutting-edge machine learning and deep learning solutions that support early warning systems and humanitarian decision-making. You will develop predictive models capable of identifying emerging crisis patterns, forecasting humanitarian needs, and transforming complex, multimodal datasets into practical insights for field operations.
This is a highly technical, hands-on role suited to someone who enjoys building, training, and fine-tuning AI models from the ground up. You are comfortable working in data-scarce, rapidly evolving environments, proactively sourcing and preparing data, and solving complex challenges where real-world impact matters.
Working closely with the AI Lead, software developers, and data engineers, you will contribute across the full machine learning lifecycle - from model development and optimisation to performance monitoring and deployment. You will also help shape the technical environment in which models are trained and refined, ensuring AI solutions are scalable, robust, and aligned with the operational realities of humanitarian response. 
What you will do:
Here are some of your specific responsibilities
<ul><li>Support the design and implementation of CLEAR&rsquo;s data architecture.
</li><li>Partner with developers and data engineers to design and stand up the environment needed to train and fine-tune models (including data ingestion pipelines, compute and GPU resources, experiment tracking and MLOps tooling) actively shaping that environment rather than waiting for it to be provided.
</li><li>Develop machine learning and deep learning models that integrate multiple data streams to detect early indicators of humanitarian crises, combining earth observation and satellite imagery, conflict event data, climate monitoring, economic indicators, and population movement patterns into unified risk assessment frameworks.
</li><li>Build computer-vision and remote-sensing models on satellite and aerial imagery (for example flood-extent mapping, building and settlement detection, displacement-site monitoring, infrastructure damage assessment and land-cover change detection) and fuse these earth observation outputs with non-imagery signals.
</li><li>Contribute to building automated alert systems that identify emerging crises, calibrating prediction algorithms for different crisis types.
</li><li>Create ensemble modelling approaches that combine traditional statistical methods with advanced AI techniques.
</li><li>Fine-tune and adapt foundation models and large language models to humanitarian use cases such as document triage, multilingual report analysis and situation summarisation.
</li><li>Explore venues for adapting models to evolving crisis conditions through reinforcement learning systems.
</li><li>Implement impact-based forecasting systems that translate meteorological, conflict, and economic predictions into specific humanitarian consequences such as displacement volumes, food insecurity levels, and infrastructure damage estimates.
</li><li>Build decision trees and recommendation engines that guide field staff through systematic needs assessment processes informed by predictive analytics and historical response data.
</li><li>Create automated reporting systems and interactive dashboards that enable field teams and leadership to access real-time data for rapid response activities.
</li><li>Any other tasks assigned by the CLEAR Technical Lead and AI Lead related to CLEAR data.
</li></ul>Please download the detailed job description to learn more about this position.
What you will bring:
<ul><li>Advanced degree in Data Science, Statistics, Computer Science, Physics, Engineering, Economics or a related quantitative field, with a minimum of 5 years of professional experience in applied data science.
</li><li>Demonstrated experience designing, training and fine-tuning deep learning models (e.g. CNNs, recurrent/sequence models and transformers), including how to structure training runs, manage compute, and diagnose and improve model performance.
</li><li>Advanced proficiency in Python for statistical analysis, machine learning and data manipulation, with experience in key libraries including pandas, NumPy, scikit-learn, TensorFlow, PyTorch and Keras.
</li><li>Strong SQL skills for database management and complex query optimization.
</li><li>Hands-on experience implementing supervised and unsupervised learning algorithms including regression models, classification techniques, clustering methods, and time series analysis.
</li><li>A proven track record of proactively sourcing and engineering data (finding, negotiating access to, cleaning and, where necessary, generating data).
</li><li>Experience designing and implementing ETL pipelines for processing datasets from multiple sources, with skills in data cleaning, transformation and quality assurance at scale.
</li><li>Ability to create automated reporting systems and dashboards using tools like Tableau, Power BI or similar platforms.
</li><li>Experience working with large, messy, real-world datasets.
</li><li>Understanding of model deployment and MLOps practices, and comfort working with engineers to provision the infrastructure models need.
</li><li>Fundamental skills with version control software and collaborative development.
</li><li>Fluency in written and spoken English. Other languages are an asset.
</li><li>Practical experience working in low-data or data-scarce settings, including transfer learning, few-shot learning, data augmentation and synthetic data generation to overcome limited training data.
</li><li>Experience implementing and fine-tuning large language models (LLMs) for applied tasks.
</li><li>Experience with natural language processing techniques for analyzing reports, social media or news data relevant to crisis monitoring.
</li><li>Experience using GenAI for automated analysis of large volumes of documents &mdash; extracting key themes, sentiment analysis and identifying emerging trends across multiple contexts and languages.
</li><li>Understanding of ensemble methods and explainable AI techniques for transparent decision-making.
</li><li>Experience working with earth observation and satellite imagery; optical (e.g. Sentinel-2, Landsat) and radar / SAR (e.g. Sentinel-1), alongside commercial high-resolution sources, and with geospatial tooling such as Google Earth Engine, rasterio / GDAL, xarray and geopandas.
</li><li>Applying computer vision and deep learning to imagery (semantic segmentation, object detection, change detection) for humanitarian tasks such as flood-extent mapping, damage assessment, settlement and displacement-site detection, infrastructure monitoring and population estimation (a strong asset).
</li><li>Experience with multimodal data fusion.
</li></ul>What we offer:
<ul><li>Duty station: Remote (Germany, France, UK or Belgium)
</li><li>Contract: Fixed term (2 years)
</li><li>Travel: Up to 10%
</li><li>Salary/benefits: Grade 9 on NRC&rsquo;s Resident salary scale, with accompanying terms and conditions.
</li><li>NRC is an equal opportunities employer. We are committed to diversity without distinction to age, gender, religion, ethnicity, nationality, and physical ability.
</li><li>We think outside the box, encourage ideas, and give responsibility to all employees at all levels. You will have many opportunities to be heard and take the initiative.
</li></ul>Find out more about the benefits of working for NRC
Important information about the application process
<ul><li>For Internal candidates: To apply as an internal candidate, log in with your official email or click on Opportunity Market Place.
</li><li>When creating your profile, include your full name as given on your passport. Complete all the system-required fields for experience, employment history and education.
</li><li>Submit your application and CV in English, taking care to attach your latest CV.
</li><li>Applications that do not meet the minimum standards in terms of experience or qualifications will generally not be considered. Unsolicited applications not related to this specific job advertisement will not be considered.
</li><li>We receive many applications for each vacant position and so only shortlisted candidates will be contacted.
</li></ul>If you have any questions about this role, please email ho.recruitment@nrc.no with the job title as the subject line.
Why NRC?
The Norwegian Refugee Council (NRC) is an independent humanitarian organisation helping people forced to flee. Our 15,000 staff work in crises across 40 countries, providing life-saving and long-term assistance to millions of people every year.
Watch this short video to see NRC in action.
We are looking for people who are passionate about helping refugees and people forced to flee. Are you one of those people? If you are, NRC offers you the opportunity to:
<ul><li>do demanding and professional work, often in challenging contexts.
</li><li>join a work culture that empowers every employee to share ideas and take responsibility.
</li><li>be part of a welcoming and supportive community committed to human dignity.</li></ul></div>
 <div><div>The Norwegian Refugee Council (NRC) is a global humanitarian organisation helping people forced to flee. 
</div><div></div> 
<div>Join us in assisting millions of people in areas where others cannot, tackling some of the world's most dangerous and difficult crises. Bring your skills and dedication to an organisation recognised for providing high quality aid and for defending the rights of refugees and internally displaced people. 
</div><div></div> 
<div>At NRC, we give responsibility to employees at all levels and foster professional growth and innovative teams. You can expect a supportive culture and an open dialogue with management. We are committed to diversity, equity and inclusion. 
</div><div></div> 
<div>Together, we save lives and rebuild futures. 
</div><div></div> 
<div>Safeguarding is central to NRC&rsquo;s work. We expect all employees to:
</div><ul><li>treat everyone with respect and dignity
</li></ul><ul><li>contribute to building a safe environment for all
</li></ul><ul><li>never engage in any form of exploitation, harassment and specifically sexual exploitation, abuse and sexual harassment (SEAH)
</li></ul><ul><li>always report. NRC has a zero-tolerance approach to inaction against exploitation, abuse and SEAH</li></ul></div>

Data Scientist

Mira

<div>
 
 About Mira
 
 
 
 Mira is a San Francisco-based hormonal health company that provides integrative care and hormonal testing to over 300,000 customers. In 2023, we were recognized by Inc. 5000 as America's fastest-growing femtech company.
 
 
 Mira&rsquo;s breakthrough innovation was creating the market&rsquo;s only FDA-compliant at-home hormone monitor with quantitative testing technology. From the beginning, our mission has been to make hormone data accessible and meaningful - so women can understand their bodies and make confident health decisions at every stage of life, from cycle health and family planning to hormonal imbalances and the menopause transition.
 
 
 We are committed to improving real health outcomes through personalized insights, cutting-edge technology, and science-backed data - turning hormone information into practical guidance for everyday wellbeing.
 
 
 
 About The Position
 
 
 
 Mira is building the future of women's hormonal health through quantitative hormone tracking technology. We're seeking an exceptional
 
 Data Scientist
 
 to be the founding member of our data science function. This is a unique opportunity to define and build the algorithmic foundation that will help millions of women better understand their reproductive health.
 
 
 As our first Data Scientist, you will own the entire research agenda - from defining what to measure and why, to building production-ready algorithms that interpret complex hormonal data across diverse populations. You'll work at the intersection of reproductive biology, machine learning, and regulated medical device development, translating cutting-edge science into features that ship in our consumer product.
 
 
 This role reports to the Head of R&amp;D and will eventually grow into leading a data science team as we scale.
 
 
 
 Requirements
 
 
 
 
 Must-have:
 
 
 
 <ul>
 <li>
 Strong Python and data science skills; SQL preferred.
 </li>
 <li>
 Experience with longitudinal, time-series, behavioral, health, wearable, physiological, or biomarker data.
 </li>
 <li>
 Experience using model interpretability and explainability methods: SHAP, LIME, etc.
 </li>
 <li>
 Experience in consumer health, digital health, wearables, diagnostics, medical devices, SaMD, or IVD.
 </li>
 <li>
 Strong model validation judgment, including handling missing data, avoiding leakage, testing robustness, and evaluating performance across user segments.
 </li>
 <li>
 Ability to translate data into user-facing product features, metrics, recommendations, or algorithms.
 </li>
 <li>
 Experience building models, scores, or analytical frameworks that influenced product, clinical, or business decisions.
 </li>
 <li>
 Strong communication skills with both technical and non-technical stakeholders.
 </li>
 <li>
 High ownership, startup speed, and comfort working with ambiguity.
 </li>
 <li>
 Good scientific judgment; able to distinguish product insights from clinical or marketing claims.
 
 
 </li>
 </ul>
 
 Nice-to-have
 
 
 
 <ul>
 <li>
 Experience with menstrual cycle, fertility, reproductive health, hormones, or women&rsquo;s health data.
 </li>
 <li>
 Advanced degree in a quantitative, biomedical, physics, or health-related field.
 </li>
 <li>
 Experience with Bayesian statistics, signal processing, causal inference, survival analysis, or longitudinal modeling.
 </li>
 <li>
 Experience moving ML or algorithmic features toward production.
 </li>
 <li>
 Familiarity with clinical validation, regulatory documentation, claim substantiation, or peer-reviewed research.
 
 
 </li>
 </ul>
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Build and improve biometrics, algorithms, and data-driven insights for the Mira App.
 </li>
 <li>
 Analyze hormone, cycle, app behavior, and user outcome data to identify patterns and product opportunities.
 </li>
 <li>
 Develop and validate models for ovulation prediction, cycle modeling, hormone interpretation, and personalized recommendations.
 </li>
 <li>
 Partner with Product, Design, Engineering, R&amp;D, and the Real-World Evidence Scientist to translate data into app features and evidence-backed insights.
 </li>
 <li>
 Support RWE and clinical research projects with data extraction, exploratory analysis, modeling, and validation.
 </li>
 <li>
 Define model-performance and validation frameworks, including uncertainty, subgroup performance, missing data, and edge cases.
 </li>
 <li>
 Improve data quality by identifying instrumentation gaps and recommending better data capture in the app.
 </li>
 <li>
 Document model logic, assumptions, limitations, and appropriate use cases clearly for technical and non-technical teams.
 </li>
 <li>
 Work with Engineering to move prototypes toward production-ready app features or data pipelines.
 
 
 </li>
 </ul>
 
 Benefits
 
 
 
 <ul>
 <li>
 Join one of the fastest-growing femtech companies in the U.S., driven by a strong mission to advance women&rsquo;s health and expand access to care
 </li>
 <li>
 Be part of a passionate, highly motivated, and international team dedicated to making a real difference in people&rsquo;s lives
 </li>
 <li>
 Thrive in a fast-paced startup environment where your work directly impacts company growth, strategy, and key decisions
 </li>
 <li>
 Enjoy real opportunities for career growth, with the ability to shape, build, and develop teams as we scale
 </li>
 <li>
 Work in a flexible, fully remote environment that supports autonomy, ownership, and independence
 </li>
 <li>
 Receive a competitive salary along with a performance-based bonus system tied to OKRs
 </li>
 </ul>
</div>

Data Scientist (Remote EU, B2B contract)

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