senior data scientist

Xenon7

<div>About us:
Where elite tech talent meets world-class opportunities!
At Xenon7, we work with leading enterprises and innovative startups on exciting, cutting-edge projects that leverage the latest technologies across various domains of IT including Data, Web, Infrastructure, AI, and many others. Our expertise in IT solutions development and on-demand resources allows us to partner with clients on transformative initiatives, driving innovation and business growth. Whether it's empowering global organizations or collaborating with trailblazing startups, we are committed to delivering advanced, impactful solutions that meet today&rsquo;s most complex challenges.
We are building a community of top-tier experts and we&rsquo;re opening the doors to an exclusive group of exceptional AI &amp; ML Professionals ready to solve real-world problems and shape the future of intelligent systems.
Location: Remote (Europe - CET) 
Experience: 5+ Years
Project Duration: ~ 2 months (B2B contract) 
Availability: Immediate Joiner
Role Overview
We are seeking a visionary and highly skilled Senior Data Scientist to lead the development of a cutting-edge document intelligence and discovery platform. This unique role sits at the intersection of advanced Generative AI, Machine Learning, and Cheminformatics. Your primary mission will be to solve a highly complex unstructured data challenge: transforming scanned PDF documents containing intricate chemical structures into highly searchable, interpretable, and actionable knowledge bases.<ul><li>
Architect Document Intelligence Solutions: Design and implement advanced Machine Learning and Deep Learning models to parse, extract, and interpret text and complex chemical structures from unstructured, scanned PDF documents.</li><li>
Develop LLM &amp; Retrieval Systems: Build and optimize Large Language Model (LLM) applications, leveraging vector databases to enable semantic search, advanced data interpretation, and retrieval-augmented generation (RAG).</li><li>
End-to-End ML Pipelines: Own the entire machine learning lifecycle, including data preprocessing (specifically for chemical data and OCR outputs), model training, evaluation, deployment, and post-deployment monitoring.</li><li>
Bridge Chemistry &amp; AI: Apply your chemistry domain knowledge to translate molecular structures, diagrams, and chemical data into machine-readable formats, embeddings, and actionable insights.</li><li>
Cloud Architecture &amp; Deployment: Deploy scalable, secure, and production-ready AI/ML pipelines within the AWS ecosystem, ensuring high availability and performance.</li><li>
Cross-Functional Collaboration: Partner closely with software engineers, data engineers, and domain experts to integrate ML models into the core product architecture and align with business goals.</li></ul> 
Requirements 
<ul><li>
Professional Experience: 5+ years of proven experience working as a Data Scientist, with a track record of delivering production-grade machine learning models.</li><li>
Domain Expertise: A strong background in Chemistry, Cheminformatics, or a highly related scientific field, with a demonstrated ability to interpret and manipulate complex chemical structures and data types.</li><li>
Core Technical Stack: Advanced proficiency in Python and deep hands-on experience with the AWS cloud stack (e.g., SageMaker, Lambda, S3, EC2).</li><li>
Generative AI &amp; Search: Practical, hands-on experience working with LLMs (fine-tuning, prompt engineering, or API integration) and vector databases (e.g., Pinecone, Milvus, Weaviate, or Qdrant).</li><li>
ML/DL Mastery: Robust experience in model development, validation, deployment, and evaluation framework tools (e.g., PyTorch, TensorFlow, Scikit-Learn).</li><li>
Document Processing (Plus): Prior experience with Computer Vision, Optical Character Recognition (OCR), or Document AI systems is highly desirable given the scanned PDF focus.</li><li>
Soft Skills: Strong analytical problem-solving skills, excellent communication, and the ability to thrive in a highly collaborative, cross-disciplinary project environment.</li></ul> 

Benefits 
At Xenon7, we're not just building AI systems&mdash;we're building a community of talent with the mindset to lead, collaborate, and innovate together.<ul><li>
Ecosystem of Opportunity: You'll be part of a growing network where client engagements, thought leadership, research collaborations, and mentorship paths are interconnected. Whether you're building solutions or nurturing the next generation of talent, this is a place to scale your influence.</li><li>
Collaborative Environment: Our culture thrives on openness, continuous learning, and engineering excellence. You'll work alongside seasoned practitioners who value smart execution and shared growth.</li><li>
Flexible &amp; Impact-Driven Work: Whether you're contributing from a client project, innovation sprint, or open-source initiative, we focus on outcomes&mdash;not hours. Autonomy, ownership, and curiosity are encouraged here.</li><li>
Talent-Led Innovation: We believe communities are strongest when built around real practitioners. Our Innovation Community isn&rsquo;t just a knowledge-sharing forum&mdash;it&rsquo;s a launchpad for members to lead new projects, co-develop tools, and shape the direction of AI itself.</li></ul></div>

Senior Data Scientist - Europe

Moss

<div>At Moss, we give finance professionals the power to automate their day-to-day and make forward-thinking decisions.
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 Sifted&rsquo;s Rising 100 and LinkedIn's Top Startups, we&rsquo;re here to help propel your career and together, make Moss a lasting success.
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).
Your responsibilities<ul><li>
Own LLM/ML pipelines for extraction, classification, anomaly detection, and recommendations.</li><li>
Define evaluation &amp; monitoring: gold sets, automated tests, robustness checks, SLAs, and cost/latency tracking.</li><li>
Productionize with Platform/Data Eng: bring your models live and iterate/improve until they are adopted by your stakeholders</li></ul>
About you<ul><li>
5-10+ years in applied ML with production ownership of shipping models/systems.</li><li>
Hands-on LLM app/agent experience (tool use/function calling, RAG, structured outputs, guardrails) in production.</li><li>
Strong Python + ML stack (e.g., scikit-learn, XGBoost/LightGBM, PyTorch/TF) and solid experiment/evaluation skills.</li></ul><ul><li>
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.</li><li>
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</li></ul>
About Moss
Moss is a SaaS scale-up founded in Berlin, with a team of 300+ people from 50+ nationalities in 5 offices across Europe.
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.
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.
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 what else to expect:<ul><li>
Top-of-market compensation package, including equity.</li><li>
Our vibrant offices are at the heart of our culture, where in-person time fuels collaboration and connection over weekly breakfasts and Friday demos.</li><li>
Additional benefits include: 20 days &ldquo;work from abroad&rdquo;, 600EUR/GBP Learning &amp; Development Budget, and other local benefits.</li></ul>
Unless stated otherwise, benefits apply to full-time positions (interns and working students receive a tailored package).
By applying for the above position, you will confirm that you have reviewed and agreed to our Data Privacy Policy.</div>

Senior Data Scientist (f/m/d)

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)

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

LimeFlight

<div>Join our fully remote, mission-driven team dedicated to pioneering sustainable inflight service management. Work on innovative technology solutions with global impact, collaborate within a diverse, international environment, and continuously enhance your skills through ongoing learning opportunities.
Headquartered in Zurich, Switzerland with team members across 11 countries, we offer a dynamic and engaging company culture that celebrates creativity, collaboration, and inclusion.
<h4 class="jobSectionHeader">About the role</h4>
We are hiring a Senior Data &amp; Analytics Engineer to take end-to-end ownership of our data platform and BI layer.
We are on a mission to contribute to a zero-waste future by drastically reducing food waste, fuel consumption, costs, and most importantly, CO₂ emissions in the airline industry. Every role in our company is a direct contributor to this vision - and as a Senior Data &amp; Analytics Engineer you will be at the forefront of turning data into meaningful insights, empowering our customers to effectively use them and drive real impact.
You will evolve a vendor-built BI solution into a modern, product-grade data platform and ensure that data is transformed into scalable, trusted, and actionable insights for both our customers and internal teams. You&rsquo;re not just building dashboards, you&rsquo;re enabling better decisions and measurable impact.
This role combines:<ul><li>
Data Engineering (pipelines, processing, customer facing exports, platform)</li><li>
Analytics Engineering (modeling, KPIs, semantic layer)</li><li>
Data Product Ownership (customer impact, insight generation)</li></ul><h4 class="jobSectionHeader">
What You&rsquo;ll Own</h4>
Platform, Architecture &amp; Pipelines
Own the end-to-end data platform (Databricks and Microsoft Fabric)<ul><li>
Design and operate scalable pipelines and lakehouse architecture</li><li>
Build scalable ETL/ELT workflows and manage batch/near real-time processing</li><li>
Ensure data quality, reliability, observability, and performance</li><li>
Define standards, data contracts, and architecture principles (clean, modular, scalable data platform)</li><li>
Optimize cost (e.g. Databricks jobs) and workload distribution across platforms</li></ul>
Data Modeling &amp; Semantic Layer<ul><li>
Own Power BI semantic models and KPIs</li><li>
Build clean, scalable dimensional models (star schema)</li><li>
Ensure performance and consistency of DAX, aggregations, and dataset refresh</li></ul>
Customer-Facing Analytics<ul><li>
Build and maintain customer-facing dashboards and embedded analytics</li><li>
Ensure consistent and trusted metrics across all outputs</li><li>
Enable self-service analytics with governance</li><li>
Maintain and monitor customer facing exports</li></ul>
Data as Product<ul><li>
Translate business and customer needs into scalable data solutions</li><li>
Define KPIs and reporting standards with Product</li><li>
Proactively build insights and identify opportunities to create additional customer value</li><li>
Drive measurable customer and business impact</li></ul>
Platform Quality, Operations, Security &amp; Governance<ul><li>
Build necessary validation scripts, unit tests, data quality checks</li><li>
Implement CI/CD, testing, and versioning for pipelines and BI</li><li>
Support multi-tenant architecture, security, and governance</li><li>
Implement monitoring and alerting (pipelines, refreshes)</li></ul>
Migration &amp; Insourcing (Initial Focus)<ul><li>
Take ownership of a vendor-built BI solution</li><li>
Reverse-engineer pipelines, logic, and reports</li><li>
Reduce technical debt and rebuild toward a clean architecture</li></ul><h4 class="jobSectionHeader">
What We&rsquo;re Looking For</h4>
Experience<ul><li>
5+ years in data engineering / analytics engineering for customer-facing BI products</li><li>
Experience in SaaS or product-driven environments</li><li>
Proven track record building scalable data platforms and customer-facing analytics</li></ul>
Technical &amp; Platform Skills<ul><li>
Strong experience with:<ul><li>
Databricks (Spark / PySpark, Delta Lake)</li><li>
Microsoft Fabric or Azure data stack</li><li>
Power BI (data modeling, DAX, performance)</li></ul></li><li>
Advanced SQL and dimensional modeling (Kimball) expertise</li><li>
Lakehouse architecture &amp; ETL/ELT design</li><li>
Multi-tenant data models &amp; embedded analytics</li></ul>
Engineering Practices<ul><li>
CI/CD for data pipelines and BI assets</li><li>
Write reusable, modular, maintainable and testable code.</li><li>
Monitoring and data quality practices</li><li>
Version control (e.g., Git)</li></ul>
Nice-to-have<ul><li>
Azure infrastructure knowledge (IAM, networking)</li><li>
Data quality/testing frameworks (e.g., Great Expectations)</li></ul>
Mindset<ul><li>
Strong ownership and autonomy: You take full ownership of outcomes, not just tasks</li><li>
Impact-driven: You focus on real-world results and have strong intuition for identifying patterns, anomalies, and optimization opportunities</li><li>
Product thinker: You connect data to user value and turn raw data into clear, actionable insights</li><li>
Proactive: You proactively identify opportunities, validate ideas, and build reports, dashboards, and analyses without waiting for requirements.</li></ul><ul><li>
Domain expert: You understand business contexts quickly and translate problems into effective data solutions.</li><li>
Pragmatic: You prioritize simplicity and avoid overengineering, focusing on what delivers value.</li><li>
Clear communicator: You communicate effectively across technical and business stakeholders, making complex topics easy to understand.</li></ul><h4 class="jobSectionHeader">
Language</h4>
Min. English C1<h4 class="jobSectionHeader">
Expected travel needs</h4>
2 annual one-week team events<h4 class="jobSectionHeader">
Our Tech Stack</h4><ul><li>
C# (.NET 8&ndash;10), ASP.NET Core, Entity Framework Core</li><li>
Microsoft SQL Server, Azure Blob Storage</li><li>
Azure App Services &amp; Functions, Docker</li><li>
Azure Service Bus, Terraform</li><li>
GitHub Actions, SonarQube, extensive unit &amp; integration tests</li><li>
Angular Latest Version</li><li>
Databricks and Azure Fabric</li></ul><h4 class="jobSectionHeader">
Hiring Process</h4><ul><li>
Recruiter Screen (45 mins)</li><li>
Interview with the Hiring Manager (1 hour)</li><li>
Technical interview (1 hour)</li><li>
Discussion with founder(s) and peer(s) (1 hour)</li></ul> 
LimeFlight is proud to be an equal opportunity employer.
We are committed to creating an inclusive environment where everyone regardless of race, ethnicity, gender identity or expression, sexual orientation, age, disability, religion, or background can thrive and do their best work.
Join us and be part of a team committed to shaping a zero-waste future for aviation, where your ideas and passion truly matter.
Let&rsquo;s talk!</div>

Senior Data & Analytics Engineer (Europe, 100% remote)

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>Junior Applied Scientist (all genders) - B2B Data Science and Algorithms
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 fulfillment experience, and we see that to do this, Machine Learning, Operations Research, and data-driven solutions will play a pivotal role.
We are seeking a highly motivated Junior Applied Scientist who is fueled by the desire to kickstart their career by building innovative and impactful ML/Optimization systems for our B2B logistics partners. You will join an established team of Senior Applied Scientists and Machine Learning Engineers, working in a cross-functional setup with Product Managers, Data Engineers, and Software Engineers.
The team&rsquo;s focus is helping our B2B partners improve inventory health and order fulfillment efficiency. With guidance and mentorship from senior team members, you will contribute to building various ML/DL forecasting models (demand, returns, lead-times), stochastic inventory optimization solutions, recommendation services, and emerging Agentic AI systems. You will play a key role in a cross-functional team where your eagerness to learn and grow will directly translate into value for our partners!
WHY YOU SHOULD BE INTERESTED&hellip;<ul><li>
Learn and Impact from Day One: You won't be stuck doing busywork. You will be an active scientific partner, working alongside experienced scientists and product teams to define problems and build solutions. Your fresh perspective will help identify new opportunities to create value for our partners.</li><li>
Tackle Complex Scientific Problems with Expert Guidance: This is your chance to bridge the gap between academia and industry. You'll tackle cutting-edge challenges in stochastic inventory optimization, multi-echelon demand forecasting, and recommender systems while receiving the mentorship needed to succeed.</li><li>
Explore Emerging Tech like Agentic AI: As we explore opening up MCP servers to our partners, you will assist in defining how we measure their performance. You will contribute to implementing evaluation frameworks (e.g., LLM-as-a-judge, safety guardrails) to ensure autonomous systems act reliably.</li><li>
Grow into End-to-End Ownership: You will have the opportunity to follow ideas from initial research and prototyping to production. You will learn how to define success metrics, collaborate with engineers to deploy scalable services, and monitor real-world impact on partner KPIs.</li><li>
Drive Impact at a Multi-Merchant Scale: Your contributions will help build platform-level services that scale across hundreds of diverse partners, 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>
Up to 2 years of hands-on experience (including internships, working student roles, or significant academic/thesis projects) applying scientific methods to solve complex problems.</li><li>
A solid theoretical foundation and practical exposure in at least one of the following areas:</li><li>
Machine Learning or Deep Learning for time-series forecasting (e.g., LGBM, ARIMA, Prophet, Transformers).</li><li>
Operations Research and Optimization (e.g., stochastic inventory models, linear/integer programming, Monte Carlo simulations).</li><li>
Machine Learning Engineering basics (e.g., understanding of git, batch processing, basic software testing).</li><li>
Agentic AI &amp; MCP evaluation frameworks</li><li>
Proficiency in SQL and Python, with some exposure to working with datasets.</li><li>
Strong communication skills with the ability to explain scientific concepts clearly and a desire to learn how to communicate effectively with business stakeholders.</li><li>
A collaborative, growth-oriented mindset. You have a passion for learning by doing and are not afraid to ask questions.</li><li>
You thrive in our team's core value: &ldquo;High Challenge, High Support&rdquo;! We cherish an open, direct feedback culture and are here to help you develop into a world-class scientist.</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<ul><li>
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.</li><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>
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>

Junior Applied Scientist (all genders)

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>
 <li>
 Work closely with fellow scientists and software engineers (at Audible and Amazon) to build and productionize models, deliver novel and highly impactful features
 </li>
 <li>
 Review models of peers for the purpose of reducing and managing risk to the business, while improving customer experience
 </li>
 <li>
 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>
 <li>
 Contribute to initiatives that employ the most recent advances in ML/AI in a fast-paced, experimental environment
 </li>
 <li>
 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

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