(senior) fullstack engineer (typescript) - client success platform (m/f/x)

(junior) cloud site reliability engineer (network) (m/f/x)

(junior) full-stack software engineer - supply chain management applications (m/f/d)

(senior) cloud engineer / linux-spezialist (m/w/d)

senior data engineer

(senior) data engineer (gn) Jobs in Berlin

(senior) data engineer (gn)

(senior) fullstack engineer (typescript) - client success platform (m/f/x) Jobs in Berlin

applied scientist, amazon robotics Jobs in Berlin

applied scientist, amazon robotics

data & ai engineer (m/w/d) Jobs in Berlin

data & ai engineer (m/w/d)

senior data scientist

Moss

<div><p><b>At Moss, we give finance professionals the power to automate their day-to-day and make forward-thinking decisions.</b></p><p><b>
Our team and culture make us unique &mdash; we&rsquo;re driven by impact and growth, where every one of us strives to learn and excel. Recognised by </b><b>Sifted&rsquo;s Rising 100</b><b> and </b><b>LinkedIn's Top Startups</b><b>, we&rsquo;re here to help propel your career and together, make Moss a lasting success.</b></p><p>
We&rsquo;re expanding our Data &amp; AI team and looking for a senior/lead contributor who has hands-on LLM app/agent experience and is fluent in classical ML. You&rsquo;ll own end-to-end LLM/ML initiatives - from problem framing and modeling to evaluation, deployment, and iteration - directly improving core product workflows (invoice understanding, approval matching, reconciliation, anomaly detection, and user-assist).</p><p></p><p><b>
Your responsibilities</b></p><ul><li><p>
Own LLM/ML pipelines for extraction, classification, anomaly detection, and recommendations.</p></li><li><p>
Define evaluation &amp; monitoring: gold sets, automated tests, robustness checks, SLAs, and cost/latency tracking.</p></li><li><p>
Productionize with Platform/Data Eng: bring your models live and iterate/improve until they are adopted by your stakeholders</p></li></ul><p></p><p><b>
About you</b></p><ul><li><p>
5-10+ years in applied ML with production ownership of shipping models/systems.</p></li><li><p>
Hands-on LLM app/agent experience (tool use/function calling, RAG, structured outputs, guardrails) in production.</p></li><li><p>
Strong Python + ML stack (e.g., scikit-learn, XGBoost/LightGBM, PyTorch/TF) and solid experiment/evaluation skills.</p></li></ul><ul><li><p>
Strategic Problem Solver: You approach ambiguous problems by deeply understanding business context and framing data science solutions that drive meaningful outcomes. You rigorously validate assumptions, identify root causes, and prioritize solving the right problem before building.</p></li><li><p>
End-to-End Executor: You independently own projects from ideation to production, balancing model performance with engineering realities. You ensure solutions are scalable, monitored, and maintained with thoughtful evaluation, deployment, and iteration strategies</p></li></ul><p><b>
About Moss</b></p><p>
Moss is a SaaS scale-up founded in Berlin, with a team of 300+ people from 50+ nationalities in 5 offices across Europe.</p><p>
Our ambition is bold: to power every SMB&rsquo;s spend across Europe - fully digital, AI-driven, and seamlessly integrated for complete control. To date, over 5000 businesses in Germany, Netherlands and the UK use Moss&rsquo; leading spend management product, with modules such as corporate cards, accounts payables, employee cash reimbursements and procurement.</p><p>
Moss has raised a total of &euro;180 million in funding and is backed by the most renowned tech investors including Valar Ventures, Tiger Global, Global Founders Capital, Cherry Ventures and A-Star.</p><p>
Be part of a culture that thrives on impact and speed, where you can take bold moves, learn fast and accomplish more. We&rsquo;re a place where you can fast track your career - here's <b>what else to expect:</b></p><ul><li><p>
Top-of-market compensation package, including equity.</p></li><li><p>
Our vibrant offices are at the heart of our culture, where in-person time fuels collaboration and connection over weekly breakfasts and Friday demos.</p></li><li><p>
Additional benefits include: 20 days &ldquo;work from abroad&rdquo;, 600EUR/GBP Learning &amp; Development Budget, and other local benefits.</p></li></ul><p><i>
Unless stated otherwise, benefits apply to full-time positions (interns and working students receive a tailored package).</i></p><p><b><i>
By applying for the above position, you will confirm that you have reviewed and agreed to our </i></b><b><i>Data Privacy Policy</i></b><b><i>.</i></b></p></div>

Senior Data Scientist (f/m/d)

Deutsche Kreditbank AG

<div><div><div><div>Senior Data Scientist - Lending &amp; ML (m/w/d)</div>
</div></div><div><div><div><div>DKB AG</div>
<div>Standort: Berlin</div>
<div>unbefristet</div>
<div>Teilzeit/Vollzeit</div>
<div>ab sofort</div></div><br>
<p></p>
<div><div><div><div><h2 class="jobSectionHeader"><b>
Dein Profil</b></h2>
</div><div><ul><li>Ein abgeschlossenes Studium der Mathematik, Physik, (Wirtschafts-)Informatik oder eines anderen quantitativen Studiengangs</li>
</ul><ul><li>Fundierte Python-Kenntnisse mit mind. 3 Jahren praktischer Erfahrung</li>
</ul><ul><li>Erfahrung mit Cloud-Diensten, idealerweise AWS, sowie in der Bereitstellung von Machine Learning Services im Unternehmenskontext</li>
</ul><ul><li>Tiefes Verst&auml;ndnis statistischer Lernverfahren und moderner Machine-Learning-Algorithmen</li>
</ul><ul><li>Pr&auml;gnante und strukturierte Ausdrucksweise</li>
</ul><ul><li>Sehr gute Deutsch- und Englischkenntnisse</li>
</ul></div></div><div><div><h2 class="jobSectionHeader"><b>Deine Aufgaben</b></h2>
</div><div><ul><li>Entwicklung leistungsf&auml;higer Services zur Optimierung von Kreditprozessen auf Basis von Machine Learning Methoden (z. B. RandomForest, xgboost, lightGBM)</li>
</ul><ul><li>Partnerschaftliche Zusammenarbeit mit Fachkolleg*innen, um Use Cases zu identifizieren und datengetriebene L&ouml;sungen mit direktem Mehrwert f&uuml;rs Kreditgesch&auml;ft umzusetzen</li>
</ul><ul><li>End-to-End-Verantwortung f&uuml;r die Entwicklung ML-basierter Services vom Proof of Concept bis zum produktiven Betrieb</li>
</ul><ul><li>Sicherstellung von Qualit&auml;t, Nachvollziehbarkeit und Robustheit der Modelle (z. B. Monitoring, Testing, Dokumentation)</li>
</ul><ul><li>Du erweiterst deine Kenntnisse regelm&auml;&szlig;ig und setzt die jeweils besten verf&uuml;gbaren Methoden f&uuml;r die Modellentwicklung ein</li>
</ul><ul><li>In einem schnell wachsenden Team kannst du deine Skills ausbauen, Verantwortung &uuml;bernehmen und deine Ideen aktiv einbringen</li></ul></div></div></div></div><br>
<p></p>
<div>
<p><i>Die DKB steht f&uuml;r Vielfalt und Chancengerechtigkeit. Egal, woher du kommst, wie alt du bist, welches Geschlecht, welche Genderidentit&auml;t, sexuelle Orientierung oder Religion du hast, ob mit oder ohne Behinderung - wir freuen uns auf deine Bewerbung!</i></p>
</div>
</div></div><div><div><div>Deine Benefits und mehr</div>
<div></div><div><ul><li><div>Attraktive Verg&uuml;tung<br>
(tariflich oder<br>
au&szlig;ertariflich)</div>
</li><div></div><li><div>Flexibles und mobiles<br>
Arbeiten &ndash; tempor&auml;r auch<br>
im EU-Ausland</div>
</li><div></div><li><div>Du hast die Wahl:
<br>
Benefits Pass, Jobticket<br>
oder Jobrad</div>
</li><div></div><li><div>Moderne Technik-<br>
ausstattung und Tool<br>
Stack</div>
</li><div></div><li><div>Individuelle Qualifi-<br>
zierungsm&ouml;glichkeiten</div>
</li><div></div><li><div>Duz-Kultur und kein<br>
Dresscode</div>
</li><div></div><li><div>Externe<br>
Mitarbeitenden-<br>
beratung</div>
</li><div></div><li><div>Angebote zum<br>
Gesundbleiben</div>
</li><div></div><li><div>Weitere Extras wie z.B.<br>
betriebliche Altersvorsorge<br>
und Versicherungsschutz</div>
</li></ul></div></div></div><div></div><div><div><div><div><div><div>Immer f&uuml;r dich ansprechbar</div>
<div>Oleg Chapaykin<br>
Expertise Lead<br>
oleg.chapaykin@dkb.de<br>
Deutsche Kreditbank AG</div></div></div></div></div></div></div><p></p>

Senior Data Scientist - Lending & ML (m/w/d)

Norwegian Refugee Council

<div><p><b>What we are looking for:
</b></p><p>We're looking for an experienced <b>Data Scientist </b>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.<br>
</p><p></p><p>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.<br>
</p><p></p><p>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.
</p><p>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.
</p><p>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.<br>
</p><p></p><p><b>What you will do:
</b></p><p><b><i>Here are some of your specific responsibilities
</i></b></p><ul><li><p>Support the design and implementation of CLEAR&rsquo;s data architecture.
</p></li><li><p>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.
</p></li><li><p>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.
</p></li><li><p>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.
</p></li><li><p>Contribute to building automated alert systems that identify emerging crises, calibrating prediction algorithms for different crisis types.
</p></li><li><p>Create ensemble modelling approaches that combine traditional statistical methods with advanced AI techniques.
</p></li><li><p>Fine-tune and adapt foundation models and large language models to humanitarian use cases such as document triage, multilingual report analysis and situation summarisation.
</p></li><li><p>Explore venues for adapting models to evolving crisis conditions through reinforcement learning systems.
</p></li><li><p>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.
</p></li><li><p>Build decision trees and recommendation engines that guide field staff through systematic needs assessment processes informed by predictive analytics and historical response data.
</p></li><li><p>Create automated reporting systems and interactive dashboards that enable field teams and leadership to access real-time data for rapid response activities.
</p></li><li><p>Any other tasks assigned by the CLEAR Technical Lead and AI Lead related to CLEAR data.
</p></li></ul><p>Please download the <b>detailed job description </b>to learn more about this position.
</p><p><b>What you will bring:
</b></p><ul><li><p>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.
</p></li><li><p>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.
</p></li><li><p>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.
</p></li><li><p>Strong SQL skills for database management and complex query optimization.
</p></li><li><p>Hands-on experience implementing supervised and unsupervised learning algorithms including regression models, classification techniques, clustering methods, and time series analysis.
</p></li><li><p>A proven track record of proactively sourcing and engineering data (finding, negotiating access to, cleaning and, where necessary, generating data).
</p></li><li><p>Experience designing and implementing ETL pipelines for processing datasets from multiple sources, with skills in data cleaning, transformation and quality assurance at scale.
</p></li><li><p>Ability to create automated reporting systems and dashboards using tools like Tableau, Power BI or similar platforms.
</p></li><li><p>Experience working with large, messy, real-world datasets.
</p></li><li><p>Understanding of model deployment and MLOps practices, and comfort working with engineers to provision the infrastructure models need.
</p></li><li><p>Fundamental skills with version control software and collaborative development.
</p></li><li><p>Fluency in written and spoken English. Other languages are an asset.
</p></li><li><p>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.
</p></li><li><p>Experience implementing and fine-tuning large language models (LLMs) for applied tasks.
</p></li><li><p>Experience with natural language processing techniques for analyzing reports, social media or news data relevant to crisis monitoring.
</p></li><li><p>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.
</p></li><li><p>Understanding of ensemble methods and explainable AI techniques for transparent decision-making.
</p></li><li><p>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.
</p></li><li><p>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).
</p></li><li><p>Experience with multimodal data fusion.
</p></li></ul><p><b>What we offer:
</b></p><ul><li><p>Duty station: Remote (Germany, France, UK or Belgium)
</p></li><li><p>Contract: Fixed term (2 years)
</p></li><li><p>Travel: Up to 10%
</p></li><li><p>Salary/benefits: Grade 9 on NRC&rsquo;s <b>Resident </b>salary scale, with accompanying terms and conditions.
</p></li><li><p>NRC is an equal opportunities employer. We are committed to diversity without distinction to age, gender, religion, ethnicity, nationality, and physical ability.
</p></li><li><p>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.
</p></li></ul><p>Find out more about the benefits of working for NRC
</p><p>Important information about the application process
</p><ul><li><p>For Internal candidates: To apply as an internal candidate, log in with your official email or click on Opportunity Market Place.
</p></li><li><p>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.
</p></li><li><p>Submit your application and CV in English, taking care to attach your latest CV.
</p></li><li><p>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.
</p></li><li><p>We receive many applications for each vacant position and so only shortlisted candidates will be contacted.
</p></li></ul><p>If you have any questions about this role, please email <b>ho.recruitment@nrc.no </b>with the job title as the subject line.
</p><p><b>Why NRC?
</b></p><p>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.
</p><p>Watch this short video to see NRC in action.
</p><p>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:
</p><ul><li><p>do demanding and professional work, often in challenging contexts.
</p></li><li><p>join a work culture that empowers every employee to share ideas and take responsibility.
</p></li><li><p>be part of a welcoming and supportive community committed to human dignity.</p></li></ul></div><p></p>
<br><div><div>The Norwegian Refugee Council (NRC) is a global humanitarian organisation helping people forced to flee.<br>
</div><div></div><br>
<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.<br>
</div><div></div><br>
<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.<br>
</div><div></div><br>
<div>Together, we save lives and rebuild futures.<br>
</div><div></div><br>
<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><p></p>

Data Scientist

Billie

<div><p>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.</p><p>
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.</p><div></div><p><b><br>
About the role:</b></p><p>
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.</p><div></div><p><b><br>
In more detail, you will:</b></p><ul><li><p>
Design and ship anti-fraud models, taking ownership of project priorities and delivering production-ready solutions.</p></li><li><p>
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.</p></li><li><p>
Balance precision and recall under severe class imbalance, explicitly weighing the cost of false positives (customer friction) against missed fraud (financial loss).</p></li><li><p>
Monitor deployed models for drift and adversarial adaptation, and retrain or recalibrate as fraud patterns shift.</p></li><li><p>
Collaborate with data and software engineers, analysts, and product managers to improve decision logic, integrate new data sources, and extend system functionality.</p></li><li><p>
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.</p></li><li><p>
Share knowledge across the team and contribute to strong experimentation and coding practices.</p></li><li><p>
Turn technical findings into clear, actionable recommendations through effective data storytelling for both technical and non-technical stakeholders.</p></li></ul><p></p><p><b>
What you bring to the team:</b></p><div></div><p><br>
Must have:</p><ul><li><p>
3-5+ years in a quantitative or machine learning role, ideally in fintech or another high-transaction environment. <b>Direct experience in fraud prevention or risk modeling is strongly preferred.</b></p></li><li><p>
Proven advanced proficiency in Python (e.g. pandas, scikit-learn, xgboost) and SQL (Snowflake, Postgres, or MySQL).</p></li><li><p>
Deep expertise in classification models (classical and deep learning), anomaly detection, and graph-based methods (e.g., graph neural networks, entity-link analysis).</p></li><li><p>
Hands-on experience productionizing ML services, with a strong grasp of modern MLOps concepts such as containerization (Docker/Kubernetes) and event-driven architectures.</p></li><li><p>
Proven ability to manage stakeholders across technical and non-technical functions, aligning technical roadmaps with business priorities.</p></li><li><p>
Sharp problem-solving skills, with the ability to translate complex business challenges into clean, efficient, and scalable technical requirements.</p></li><li><p>
Strong communication skills, with a track record of using data to influence strategy and drive cross-functional engagement.</p></li></ul><p></p><p>
Nice to have:</p><ul><li><p>
Experience with ML orchestration frameworks such as Metaflow, Apache Flink, or similar MLOps tooling.</p></li><li><p>
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.</p></li></ul><p><b>
What We Offer:</b></p><ul><li><p>
Challenging and impactful work that drives personal and professional growth</p></li><li><p>
One of the best Virtual Shares Incentive Programs in the market, so that everyone at Billie is invested in our success</p></li><li><p>
Flexible work hours and trust in your ability to deliver, empowering you to take control of your work-life balance</p></li><li><p>
A hybrid working approach that allows you to work from home for up to 3 days per week</p></li><li><p>
Enjoy 30 days vacation per year, sabbatical opportunities, and extra child sickness leave for parents.</p></li><li><p>
Our &ldquo;Catch a Ride with Billie&rdquo; program that enables discounted access to Berlin Public Transport (BVG), Deutschland-Ticket, OR JobRad</p></li><li><p>
A yearly development budget to broaden your skill set and horizons</p></li><li><p>
Free German group classes</p></li><li><p>
An English-speaking, multicultural team with more than 40 nationalities</p></li><li><p>
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!</p></li></ul><p><i>
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.</i></p><p>
For information about data processing see our &quot;Recruiting Privacy Policy and further information&quot;: https://www.billie.io/en/candidate-information</p></div>

Fraud Data Scientist

The Quality Group

<p></p><div><p>Start: Immediately | Level: Mid - Senior | Location: Germany, remote | Working Hours: Full Time (40h/Week)</p><br>
<p>
We're looking for a (Senior) Data Engineer (gn) who's ready to leave a real mark. You'll take ownership of our data platform, drive the architecture of scalable and reliable data products &ndash; and play a central role in shaping our Data Warehouse to the next level. As the core of our data hub, you'll connect teams, technologies, and insights, setting the technical direction for how we work with data across the entire organisation.</p>
<h3 class="jobSectionHeader"><b>
Your mission</b></h3>
<ul><li>You design and own the architecture of our end-to-end data platform, including ingestion, transformation, and serving layers</li>
<li>You lead the development of robust data pipelines using Fivetran, Airbyte, and Python &ndash; setting engineering standards for the team</li>
<li>You drive data modeling excellence in Databricks using advanced SQL, dbt, and data quality frameworks like elementary</li>
<li>You define and enforce data quality standards, ensuring reliable data marts that power business-critical decisions</li>
<li>You act as technical lead, collaborating closely with the Product Owner and Business Insights team on complex data challenges</li>
<li>You own and evolve our cloud infrastructure on AWS, driving infrastructure-as-code with Terraform (IaC)</li></ul><p><br>
</p><h3 class="jobSectionHeader"><b>Your experience &amp; skills</b></h3>
<ul><li>You have several years of hands-on experience as a Data Engineer, ideally in a cloud-native environment</li>
<li>You're proficient in SQL, Python, dbt, and Git &ndash; and have a strong track record of building production-grade pipelines</li>
<li>You bring experience with cloud platforms (AWS preferred) and tools like Databricks, Fivetran, or Airbyte</li>
<li>You have a deep understanding of data modeling, data warehouse design, and data quality best practices</li>
<li>You're a strong communicator who can bridge the gap between engineering and business stakeholders</li>
<li>You're self-driven, take ownership end-to-end, and thrive in a remote, async-first environment</li>
</ul><h3 class="jobSectionHeader"><b>Why choose us?</b></h3>
<p>
Being part of our team means joining a high-performing company with a diverse and inclusive culture. In our fast-growing team of over 1,200 employees, we combine our passion for sports nutrition, supplements, and healthy foods with cutting-edge technology, production, and logistics processes. All of this serves one goal: providing our customers with top-quality products to support their healthy and active lifestyle.</p>
<p>
You can look forward to a strong sense of team spirit, ongoing opportunities for professional growth and responsibility, and an exciting work environment that blends lifestyle and career. With locations in Hamburg, Elmshorn, Kaltenkirchen/N&uuml;tzen, and Elsdorf, TQG offers diverse career opportunities in areas such as technology, product development, sales, marketing, and logistics. Additionally, you'll benefit from:</p>
<ul>
<li>Flexible working hours and remote work options</li>
<li>Attractive employee discounts</li>
<li>Subsidy for the E-gym Wellpass</li>
<li>Workation</li>
<li>Corporate benefits</li>
<li>28 days vacation/year</li>
<li>and much more</li></ul><br>
<p></p>
<h3 class="jobSectionHeader"><b>
About Us</b></h3>
<p>
The Quality Group (TQG) is an innovative provider of sports nutrition products, bringing together the successful brands <b>ESN </b>and <b>More Nutrition </b>since 2021.</p>
<p><b>
ESN </b>has been the German market leader in sports nutrition since 2004, offering products like protein powders, bars, and supplements designed for ambitious fitness goals. Founded in 2017, <b>More Nutrition</b> focuses on healthy, reduced-sugar foods, providing solutions for conscious nutrition and weight management without compromise.</p>
<p>
TQG's vision is to help people become the best version of themselves. With passion and innovation, the company develops high-quality products that promote health, performance, and joy in life. Its agile company culture and exciting career opportunities make TQG a strong partner not only for customers but also for employees.</p>
<p><b>
This is us &ndash; The Quality Group &ndash; nice to meet you! Now it's your turn!</b><br>
We look forward to your application! Regardless of gender, age, background, or identity &ndash; what matters to us is who you are and what you bring to the table. Join our team and grow with us!</p></div><p></p>

(Senior) Data Engineer (gn)

Charité - Universitätsmedizin Berlin

<div>
 Jetzt bewerben
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 <br/>
 https://karriere.charite.de/stellenangebote/detail/7354
 <br/>
 <br/>
 Arbeitszeit
 <br/>
 <br/>
 <strong>
  Teilzeit
  <br/>
  <br/>
 </strong>
 Eintrittsdatum
 <br/>
 <br/>
 <strong>
  15.06.2026
  <br/>
  <br/>
 </strong>
 Dauer der Anstellung
 <br/>
 <br/>
 <strong>
  Befristet
  <br/>
  <br/>
 </strong>
 Bewerbungsfrist
 <br/>
 <br/>
 <strong>
  06.07.2026
  <br/>
  <br/>
 </strong>
 Einsatzort Charit&eacute;
 <br/>
 <br/>
 <strong>
  Campus Charit&eacute; Mitte
  <br/>
  <br/>
 </strong>
 Kennziffer
 <br/>
 <br/>
 <strong>
  7354
  <br/>
  <br/>
 </strong>
 Entgeltgruppe
 <br/>
 <br/>
 <strong>
  E13
  <br/>
  <br/>
 </strong>
 <strong>
  Arbeiten an der Charit&eacute;
  <br/>
  <br/>
 </strong>
 Der Giftnotruf der Charit&eacute; ist das zust&auml;ndige Giftinformationszentrum f&uuml;r Berlin und Brandenburg und unterst&uuml;tzt als telemedizinisches Fachzentrum bei Vergiftungen. Wir beraten Bev&ouml;lkerung und medizinisches Fachpersonal nach Vergiftungen und sind damit ein wichtiger Akteur in der Toxikovigilanz und Risikosurveillance. Professionalle Datenauswertung unterst&uuml;tzt die fundierte Notfallberatung und identifiziert Pr&auml;ventionsgebiete und Risikogruppen - und legt die Basis f&uuml;r den Gesamtauftrag im Gesundheitsschutz
 <br/>
 <br/>
 <strong>
  Die Stelle im &Uuml;berblick
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Zu Ihren Aufgaben z&auml;hlen die retrospektive Auswertung der Beratungen im Giftnotruf der Charit&eacute; und die strukturierte Validierung der Daten
  </li>
  <li>
   Sie sind f&uuml;r die belastbare Datenbasis verantwortlich, die zum Aufbau eines Berichtswesens an Beh&ouml;rden, Organisationen und weitere &ouml;ffentliche Einrichtungen dient.
  </li>
  <li>
   Bei der Erstellung und Pr&uuml;fung von Berichten unterst&uuml;tzen sie unmittelbar
  </li>
  <li>
   Sie wirken mit bei der Datenanalyse zu wissenschaftlichen Publikationen
  </li>
  <li>
   Sie begleiten durch die kontinuierliche Datenauswertung die interne Qualit&auml;tskontrolle und tragen damit zu einer Verbesserung der Beratung und Dokumentation bei
  </li>
  <li>
   Die Stelle ist projektbegleitend und daher auf 2 Jahre befristet
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Danach suchen wir
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Sie verf&uuml;gen &uuml;ber ein abgeschlossenes Masterstudium im Bereich der Toxikologie.
  </li>
  <li>
   Berufserfahrung in einem Giftinformationszentrum konnten Sie bereits sammeln
  </li>
  <li>
   Fundierte Kenntnisse in Toxikologie und Dateninterpretation z&auml;hlen zu Ihren St&auml;rken
  </li>
  <li>
   Sie sind sicher im Umgang mit MS Excel, SAP Hana Datenbankabfragen, KNIME und statistischer Auswertung mit R, SPSS oder vergleichbarer Software
  </li>
  <li>
   Eine selbstst&auml;ndige, digital affine Arbeitsweise pr&auml;gt Ihr t&auml;gliches Handeln
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Das bringt die Charit&eacute; mit
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Eine zukunftsorientierte, abwechslungsreiche und anspruchsvolle T&auml;tigkeit mit hoher Eigenverantwortung und pers&ouml;nlichem Handlungsspielraum
  </li>
  <li>
   Eine zus&auml;tzliche Absicherung im Alter durch unsere betriebliche Altersvorsorge
  </li>
  <li>
   Seit 2007 zertifiziert als familiengerechte Hochschule und familiengerechtes Unternehmen - Weitere Informationen finden Sie hier
  </li>
  <li>
   Ber&uuml;cksichtigung von Dienstplanw&uuml;nschen
  </li>
  <li>
   Nach Einarbeiten ist in Abstimmung Homeoffice m&ouml;glich
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Informationen zur Stelle
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Entgeltgruppe E13 TV&ouml;D VKA-K. Hier finden Sie alle Informationen zum Gehalt und Tarifvertrag
  </li>
  <li>
   Die Arbeitszeit ist in Teilzeit mit 28,86 Stunden (75%)
  </li>
  <li>
   Die Position ist bis zum 28.06.2028 befristet, da sie an die Projektlaufzeit gebunden ist
  </li>
  <li>
   Bei uns sind 30 Tage Urlaub Standard
  </li>
  <li>
   Die Bewerbungsfrist endet am: 06.07.2026
  </li>
  <li>
   Kennziffer: 7354
   <br/>
   <br/>
  </li>
 </ul>
 Bewerbung
 <br/>
 <br/>
 An der Charit&eacute; sind alle willkommen, unabh&auml;ngig von Alter, Religion, Geschlecht, geschlechtlicher Identit&auml;t, sexueller Orientierung, Nationalit&auml;t, Behinderung, ethnischer oder sozialer Herkunft. Hier z&auml;hlt jeder Mensch! Wir setzen uns f&uuml;r Chancengleichheit und Inklusion ein.
 <br/>
 <br/>
 Aus Datenschutzgr&uuml;nden nehmen wir Bewerbungen ausschlie&szlig;lich &uuml;ber unser Bewerbungsportal entgegen. Der unten angegebene Kontakt steht ausschlie&szlig;lich f&uuml;r R&uuml;ckfragen zur Verf&uuml;gung.
 <br/>
 <br/>
 Jetzt bewerben
 <br/>
 <br/>
 <strong>
  Bei Fragen Wenden Sie Sich Bitte An
  <br/>
  <br/>
 </strong>
 Frau Martina Hahn Nimmergut
 <br/>
 <br/>
 Teamleitung Firmenservice
 <br/>
 <br/>
 martina.hahn@charite.de
 <br/>
 <br/>
 030 450 569702
 <br/>
 <br/>
 Vorteile und Leistungen
 <br/>
 <br/>
 Faire L&ouml;hne und Arbeitskonditionen
 <br/>
 <br/>
 An der Charit&eacute; erwarten dich Tarifvertr&auml;ge mit fairem Gehalt, vielf&auml;ltigen Zusatzleistungen und 30 Tagen Urlaub. Die aktuellen Tarifvertr&auml;ge und Entgelttabellen findest du hier.
 <br/>
 <br/>
 Familie und Beruf sind an der Charit&eacute; vereinbar
 <br/>
 <br/>
 Unsere Anlaufstellen bieten eine pers&ouml;nliche Beratung, um die Vereinbarkeit von Beruf und Familie sicherzustellen. Auch im Fall von pflegebed&uuml;rftigen Angeh&ouml;rigen. Zudem organisieren wir Kinderbetreuung in Ferienzeiten und kooperieren mit Kitas.
 <br/>
 <br/>
 Leben und Arbeiten in Berlin
 <br/>
 <br/>
 Wir haben vier zentrale Einsatzorte in Berlin. Gute Verkehrsanbindungen sowie vielf&auml;ltigste Kultur- und Freizeitangebote machen das Leben hier besonders attraktiv.
 <br/>
 <br/>
 Weitere Vorteile
 <br/>
 <br/>
 H&auml;ufig gestellte Fragen
 <br/>
 <br/>
 Besteht die M&ouml;glichkeit, im Homeoffice zu arbeiten?
 <br/>
 <br/>
 Grunds&auml;tzlich besteht die M&ouml;glichkeit, im Homeoffice zu arbeiten. Diese ist jedoch vom jeweiligen Bereich und Aufgabenfeld abh&auml;ngig. Sprich hierzu gerne mit der Ansprechperson des Bereichs, f&uuml;r den du dich interessierst.
 <br/>
 <br/>
 Wie werde ich verg&uuml;tet?
 <br/>
 <br/>
 Bei uns wirst du fair und transparent nach Tarifvertrag verg&uuml;tet &ndash; 30 Tage Urlaub inklusive. Die Tarifvertr&auml;ge und Entgelttabellen findest du hier.
 <br/>
 <br/>
 Gibt es auch die M&ouml;glichkeit, in Teilzeit zu arbeiten?
 <br/>
 <br/>
 Generell bieten wir immer auch die M&ouml;glichkeit, in Teilzeit zu arbeiten. Ob und in welcher Form besprichst du am besten direkt mit deiner Ansprechpartnerin oder Ansprechpartner.
 <br/>
 <br/>
 Weitere Fragen und Antworten
 <br/>
 <br/>
 Weitere Informationen
 <br/>
 <br/>
 Datenschutzhinweise
 <br/>
 <br/>
 Die Charit&eacute; weist darauf hin, dass im Rahmen und zu Zwecken des Bewerbungsverfahrens an verschiedenen Stellen in der Charit&eacute; (z.B. Fachbereich, Personalvertretung, Personalabteilung) personenbezogene Daten gespeichert und verarbeitet werden. Weiterhin k&ouml;nnen die Daten innerhalb des Konzerns sowie an Stellen au&szlig;erhalb (z.B. Beh&ouml;rden) zur Wahrung berechtigter Interessen &uuml;bermittelt bzw. verarbeitet werden. Mit Ihrer Bewerbung stimmen Sie unseren Datenschutz- und Nutzungsbestimmungen f&uuml;r Bewerbungsverfahren, die Sie hier finden, zu.
 <br/>
 <br/>
 Zusatzinformationen
 <br/>
 <br/>
 Die Charit&eacute; &ndash; Universit&auml;tsmedizin Berlin trifft ihre Personalentscheidungen nach Eignung, Bef&auml;higung und fachlicher Leistung. Die Charit&eacute; strebt eine Erh&ouml;hung des Anteils von Frauen in F&uuml;hrungspositionen an und fordert Frauen daher nachdr&uuml;cklich auf, sich zu bewerben. Bei gleichwertiger Qualifikation werden Frauen im Rahmen der rechtlichen M&ouml;glichkeiten vorrangig ber&uuml;cksichtigt. Bewerbungen von Menschen mit Migrationshintergrund, die die Einstellungsvoraussetzungen erf&uuml;llen, sind ausdr&uuml;cklich erw&uuml;nscht. Schwerbehinderte Bewerber:innen werden bei gleicher Qualifikation bevorzugt. Bei der Einstellung wird ein polizeiliches F&uuml;hrungszeugnis, teilweise ein erweitertes F&uuml;hrungszeugnis verlangt. Die Bewerbungsunterlagen k&ouml;nnen leider nur dann zur&uuml;ckgeschickt werden, wenn ein ausreichend frankierter R&uuml;ckumschlag beigef&uuml;gt ist. Eventuell anfallende Reisekosten k&ouml;nnen nicht erstattet werden.
</div>


Data Scientist im Giftnotruf (d/w/m)

Zeta Global

<div>
 <p>
  &nbsp;
 </p>
 <p>
  <strong>
   WHO WE ARE&nbsp;
  </strong>
 </p>
 <p>
  Zeta Global (NYSE: ZETA) is the AI-Powered Marketing Cloud that leverages advanced artificial intelligence (AI) and trillions of consumer signals to make it easier for marketers to acquire, grow, and retain customers more efficiently. Through the Zeta Marketing Platform (ZMP), our vision is to make sophisticated marketing simple by unifying identity, intelligence, and omnichannel activation into a single platform &ndash; powered by one of the industry&rsquo;s largest proprietary databases and AI. Our enterprise customers across multiple verticals are empowered to personalize experiences with consumers at an individual level across every channel, delivering better results for marketing programs. Zeta was founded in 2007 by David A. Steinberg and John Sculley and is headquartered in New York City with offices around the world. To learn more, go to www.zetaglobal.com.
 </p>
 <p>
  &nbsp;
 </p>
 <p>
  <strong>
   The Role
  </strong>
 </p>
 <p>
  We&rsquo;re looking for a skilled&nbsp;
  <strong>
   ML Engineer / Data Scientist
  </strong>
  &nbsp;with&nbsp;
  <strong>
   3+ years of software or applied ML experience
  </strong>
  &nbsp;to design, build, and improve machine learning solutions in a dynamic cloud environment, primarily on&nbsp;
  <strong>
   AWS
  </strong>
  .This role sits at the intersection of&nbsp;
  <strong>
   data science and engineering
  </strong>
  : exploring data, developing models, running rigorous experiments, and bringing the best approaches into production with a reliable, reproducible workflow. If strong Python skills, curiosity about hard modeling problems, and collaborative work in multicultural teams are a fit, this is a chance to do meaningful, end-to-end ML work&mdash;not just notebooks, and not just infrastructure.
 </p>
 <p>
  &nbsp;
 </p>
 <p>
  <strong>
   Who you are:
  </strong>
 </p>
 <ul>
  <li>
   Strong foundation in&nbsp;
   <strong>
    machine learning,&nbsp;statistics
   </strong>
   and&nbsp;
   <strong>
    experiment design
   </strong>
   .
  </li>
  <li>
   Experience building models for&nbsp;
   <strong>
    real business or product problems
   </strong>
   , not only academic benchmarks.
  </li>
  <li>
   Comfortable working with&nbsp;
   <strong>
    structured and unstructured data
   </strong>
   : feature engineering, dataset construction, labeling quality, leakage checks, and train/validation/test discipline.
  </li>
  <li>
   Able to compare approaches with clear&nbsp;
   <strong>
    metrics
   </strong>
   , error analysis, and sound judgment about tradeoffs (accuracy, latency, cost, maintainability).
  </li>
  <li>
   Interest in&nbsp;
   <strong>
    modern ML
   </strong>
   , including classical ML, deep learning, and&nbsp;
   <strong>
    LLM / GenAI workflows
   </strong>
   &nbsp;where relevant (fine-tuning, RAG, evaluation, prompt/versioning).
  </li>
  <li>
   Proficient in&nbsp;
   <strong>
    Python
   </strong>
   &nbsp;and able to write&nbsp;
   <strong>
    clean, modular, testable&nbsp;code
   </strong>
   .
  </li>
  <li>
   Experience developing and deploying ML solutions in a&nbsp;
   <strong>
    cloud environment
   </strong>
   , especially&nbsp;AWS.
  </li>
  <li>
   Comfortable moving from prototype to production: packaging models, building inference paths, monitoring performance, and iterating after launch.
  </li>
  <li>
   Independent engineer who can own work from&nbsp;
   <strong>
    problem framing &rarr; experimentation &rarr; implementation &rarr; rollout
   </strong>
   .
  </li>
  <li>
   Excellent&nbsp;
   <strong>
    written and spoken English
   </strong>
   .
  </li>
  <li>
   Enjoy working closely with engineers, product partners, and other data scientists.
  </li>
  <li>
   Clear communicator who can explain methods, results, and limitations to technical and non-technical audiences.
  </li>
  <li>
   <strong>
    Master&rsquo;s degree
   </strong>
   &nbsp;in Science or Engineering (Computer Science, Mathematics, Physics, Statistics, or similar),&nbsp;
   <strong>
    or equivalent practical experience
   </strong>
   .
  </li>
 </ul>
 <p>
  <strong>
   Nice to have:
  </strong>
 </p>
 <ul>
  <li>
   Experience with&nbsp;
   <strong>
    scikit-learn,&nbsp;PyTorch,&nbsp;TensorFlow,&nbsp;XGBoost
   </strong>
   , or similar modeling stacks.
  </li>
  <li>
   Familiarity with&nbsp;
   <strong>
    ML experiment tracking
   </strong>
   &nbsp;and reproducibility (e.g. MLflow, W&amp;B).
  </li>
  <li>
   Experience with&nbsp;
   <strong>
    SQL
   </strong>
   , data warehouses/lakes, and pipeline tools such as&nbsp;
   <strong>
    Airflow,&nbsp;dbt, or&nbsp;Spark
   </strong>
   .
  </li>
  <li>
   Exposure to&nbsp;
   <strong>
    feature stores
   </strong>
   , embedding pipelines, or&nbsp;
   <strong>
    vector search
   </strong>
   &nbsp;for retrieval-based systems.
  </li>
  <li>
   Experience building&nbsp;
   <strong>
    HTTP/gRPC APIs
   </strong>
   &nbsp;or lightweight services around model inference.
  </li>
  <li>
   Working knowledge of&nbsp;
   <strong>
    Docker
   </strong>
   , basic orchestration, and CI/CD (e.g.&nbsp;
   <strong>
    GitLab CI
   </strong>
   ).
  </li>
  <li>
   Experience in&nbsp;
   <strong>
    agile
   </strong>
   ,&nbsp;
   <strong>
    remote
   </strong>
   and&nbsp;
   <strong>
    async
   </strong>
   &nbsp;team environments.
  </li>
  <li>
   Publications, patents, Kaggle/competition results, or open-source ML contributions.
  </li>
 </ul>
 <p>
  <strong>
   What you might like about this role:
  </strong>
 </p>
 <ul>
  <li>
   <strong>
    Hands-on modeling work
   </strong>
   &nbsp;with room to explore, benchmark, and improve real systems.
  </li>
  <li>
   Collaboration on&nbsp;
   <strong>
    ML patent submissions
   </strong>
   &nbsp;and participation in&nbsp;weekly ML / research paper review&nbsp;meetings.
  </li>
  <li>
   A&nbsp;
   <strong>
    multicultural, engineering-focused team
   </strong>
   &nbsp;with strong peer support.
  </li>
  <li>
   <strong>
    High trust and autonomy
   </strong>
   &mdash;clear goals, freedom in how to reach them.
  </li>
  <li>
   <strong>
    Internal product impact
   </strong>
   : meaningful projects that improve developer and user experience, not endless maintenance tickets.
  </li>
  <li>
   <strong>
    Short approval cycles
   </strong>
   &nbsp;and solid product partnership.
  </li>
  <li>
   A&nbsp;
   <strong>
    healthy meeting policy&nbsp;
   </strong>
   and emphasis on protecting focus time.
  </li>
  <li>
   <strong>
    Flexible hours
   </strong>
   , remote/home office options, and a calm, engineers-only office when on-site.
  </li>
  <li>
   <strong>
    Competitive compensation
   </strong>
   , including&nbsp;stock options.
  </li>
 </ul>
 &nbsp;
 <p>
  We&rsquo;re hiring across
  <strong>
   multiple levels
  </strong>
  . Title, scope, and compensation depend on experience&mdash;from strong applied ML generalists to senior people who can lead modeling direction and mentor others.
 </p>
 <p>
  We&rsquo;re especially interested in candidates who are&nbsp;
  <strong>
   technically strong, intellectually curious, and motivated by difficult, ambiguous problems
  </strong>
  &nbsp;where good data science and solid engineering both matter.
 </p>
 <p>
  &nbsp;
 </p>
 <p>
  &nbsp;
 </p>
 <p>
  <strong>
   PEOPLE &amp; CULTURE AT ZETA
  </strong>
 </p>
 <p>
  Zeta considers applicants for employment without regard to, and does not discriminate on the basis of an individual&rsquo;s sex, race, color, religion, age, disability, status as a veteran, or national or ethnic origin; nor does Zeta discriminate on the basis of sexual orientation, gender identity or expression.&nbsp;&nbsp;
 </p>
 <p>
  We&rsquo;re committed to building a workplace culture of trust and belonging, so everyone feels invited to bring their whole selves to work. We provide a forum for employees to celebrate, support and advocate for one another. Learn more about our commitment to diversity, equity and inclusion here:&nbsp; https://zetaglobal.com/blog/a-look-into-zetas-ergs/&nbsp;
 </p>
 <p>
  <strong>
   ZETA IN THE NEWS!
  </strong>
 </p>
 <p>
  https://zetaglobal.com/press/?cat=press-releases&nbsp;
 </p>
 <p>
  &nbsp;
 </p>
 <p>
 </p>
 <span>
 </span>
</div>


ML Ops Engineer

Explore 84+ Senior data scientist in Berlin this July. Find roles across top companies and apply now to boost your career.