Forward Deployed Data Scientist at Braze | Paris

Join our team as a Data Scientist and play a key role in managing and optimizing Large Language Models (LLMs) for AI safety.About UsWhite Circle is a pioneering AI Safety company dedicated to enhancing the safety, reliability, and efficiency of AI systems. Our platform is built on policies—clear natural language rules that dictate the appropriate conduct of AI models. We automate the testing, enforcement, and continuous enhancement of these policies at scale.We have secured $11 million in funding from leading investors, including founders and senior leaders from OpenAI, Anthropic, HuggingFace, Mistral, DeepMind, Datadog, Sentry, and others.Our operations handle over 100 million API calls each month.We specialize in fine-tuning and training our own LLMs, enabling them to operate faster and at a lower cost than any available model.As a compact and dedicated team, we offer an environment where you can tackle complex challenges, expedite your work into production, and substantially influence the development of AI safety.Your Role:Transform vast amounts of unstructured text into a structured and navigable format (including topics, clusters, segments, trends, and anomalies), moving from “unknown unknowns” to stable definitions for tracking.Develop scalable representation pipelines: including sampling strategies, preprocessing/normalization, embeddings at scale, indexing, and retrieval, making the corpus searchable and analyzable.Utilize LLMs in practical applications: implementing labeling/classification, weak supervision, data enrichment, summarization, and automated diagnostics of incoming volumes, with cost and quality controls in place.Provide actionable insights that inform decisions: convert your findings into product and operational strategies (identifying available data, gaps, quality issues, and prioritization).Create self-service analytics resources: develop datasets, data models, and user-friendly tools/dashboards to enable team members to explore and address inquiries independently.Collaborate closely with engineering and research teams: ensure alignment of pipelines with production constraints (including latency, cost, and privacy) and integrate outputs into existing workflows.You Will Thrive If You:Possess strong skills in Python and SQL, with an engineering mindset capable of building reliable pipelines rather than just notebooks.Have practical experience in applied NLP/ML on real-world text: including embeddings, clustering, and model training.

Overview: We are seeking a talented Data Engineer to architect and develop our data pipelines from the ground up—managing petabytes of logs, events, and model traces—while establishing a seamless, reliable environment for production, testing, and research tasks.About UsAt White Circle, we focus on AI Safety by creating a robust layer that ensures the safety, reliability, and optimization of AI systems. Our platform is driven by policies, which are straightforward natural-language rules that specify the acceptable behaviors of AI models. We automatically test, enforce, and enhance these policies at scale.We have successfully raised $11M from leading investors, including founders and executives from OpenAI, Anthropic, HuggingFace, Mistral, DeepMind, Datadog, and Sentry.Our system handles over 100 million API calls every month.We develop and fine-tune our own Large Language Models (LLMs) to ensure they operate faster and more economically than any open-source or proprietary alternatives.As a small, dedicated team, we value deep engagement with challenging problems, rapid deployment of your contributions, and the opportunity to significantly impact the construction of AI safety.Your ResponsibilitiesEstablish and uphold a clean and stable data environment, allowing team members to access petabytes of traces, logs, and model outputs in their required formats without delays or manual extraction.Create and manage internal data APIs, SDKs, and tools that empower engineering, product, and research teams to explore, query, and utilize data independently of infrastructure concerns.Monitor and enhance data performance, optimizing table layouts and query plans to ensure smooth analytics and research workflows as data volumes increase.Oversee data access and governance by defining and enforcing permissions, access rules, and security protocols.Desired QualificationsProven experience building or scaling a modern data stack—such as Snowflake, ClickHouse, or event streaming—within a startup or similarly fast-paced environment.Strong proficiency in SQL and Python, with the ability to work effectively with large, complex datasets.Excellent communication skills, enabling you to collaborate directly with engineers and researchers. Fluency in English is required.Bonus: Experience with data visualization tools like Metabase, Tableau, or similar.

Overview: We are seeking a talented Product Engineer specializing in Backend Development with Rust to take charge of and enhance the foundational systems that ensure AI safety at a large scale. Your role will involve constructing APIs capable of managing hundreds of millions of requests, implementing real-time policy enforcement, and developing high-throughput data pipelines.About UsWhite Circle is at the forefront of AI Safety, creating the essential safety, reliability, and optimization framework for AI systems. Our platform is built on policies—easily understandable natural-language rules that outline appropriate AI model behavior. We automatically test, enforce, and continuously refine these policies on a massive scale.We have secured $11M in funding from leading investors, founders, and executives from OpenAI, Anthropic, HuggingFace, Mistral, DeepMind, Datadog, Sentry, and others.Our systems process over one hundred million API calls each month.We optimize and train our own LLMs to operate more swiftly and cost-effectively than any publicly available or proprietary models.As a compact and highly focused team, we welcome those eager to tackle challenging problems, deliver their work to production swiftly, and actively shape the future of AI safety.Your Responsibilities:Design and implement backend services in Rust that facilitate real-time policy evaluations at scale, ensuring low latency and high reliability.Take ownership of features from inception to deployment: API design, database schema development, and continuous monitoring and iteration.Engage with different layers of the stack as needed; we prioritize problem-solving over rigid role definitions.Enhance system performance and reliability through connection pooling, caching strategies, query optimization, and observability practices.Collaborate directly with product managers, researchers, and ML teams to convert requirements into effective production systems.Ideal Candidate:You have experience building and deploying backend systems in Rust—beyond mere tutorials, you have real-world production experience.You are well-versed in async Rust (Tokio), web frameworks (Axum, Actix), and database interaction patterns.You possess strong system design fundamentals, capable of assessing trade-offs, failure modes, and scalability.You have hands-on experience with PostgreSQL, adept at crafting efficient queries and designing schemas.

Overview: We are on the hunt for a skilled DevOps Engineer to architect and sustain the cloud and on-premise infrastructure that powers our innovative platform. Your responsibilities will span Kubernetes clusters, CI/CD pipelines, observability, networking, and automation, ensuring our production environment is reliable, secure, and scalable.About White CircleWhite Circle is dedicated to AI Safety, developing a framework that guarantees the safety, reliability, and efficiency of AI systems. Central to our platform are policies—clear, natural-language guidelines that dictate the permissible actions of AI models. We automate the testing, enforcement, and enhancement of these policies at scale.We have successfully secured $11M in funding from industry leaders and top-tier investors, including veterans from OpenAI, Anthropic, HuggingFace, and more.Our systems handle over one hundred million API calls each month.We specialize in fine-tuning and training our own LLMs for optimal performance and cost-efficiency compared to existing models.As a small, focused team, we value deep engagement with challenging problems. If you’re eager to see your contributions rapidly deployed into production and influence the future of AI safety, we want to hear from you.Your Responsibilities:Design, develop, and maintain production infrastructure in AWS and on-premise environments.Oversee and enhance Kubernetes clusters for deployment, scalability, reliability, and daily operations.Develop and maintain CI/CD pipelines to facilitate safer, quicker, and more reliable software releases.Manage container infrastructure, focusing on Docker image management, runtime security, and overall lifecycle.Increase system reliability, performance, and observability through rigorous monitoring, alerting, and troubleshooting.Implement infrastructure as code using Terraform for consistent and adaptable environments.Manage networking across the stack, including routing, firewalls, load balancing, and inter-cluster communication.Automate processes and enhance workflows using Python scripts and internal tools.Collaborate with engineering and ML teams to bolster product infrastructure, internal platforms, and compute-intensive workloads.Ideal Candidate:Possesses a strong background in cloud infrastructure, particularly AWS.Demonstrates expertise in Kubernetes and CI/CD practices.Is proficient in Python and Terraform.Exhibits a solid understanding of networking concepts.Thrives in a collaborative, fast-paced environment.

Our Mission:At Avisia, we engage with our clients on 100% data-driven projects that merge technical and operational dimensions. Depending on your profile and interests, you will have the opportunity to work on projects addressing purely technical challenges or more business-oriented issues.Our clients span a variety of industries including Luxury, Retail, Telecom, Banking, and Insurance. The data science projects you may be involved in will also cover diverse topics.Current project examples include:Developing revenue forecasting models for an e-commerce retailer. #ForecastingCreating and industrializing a recommendation engine to enhance website visitor conversion rates. #RecommendationEstablishing an attrition score to identify slowly declining customers for a large retail chain. #ChurnImplementing customer segmentation to optimize marketing and sales actions based on channel contact preferences. #CustomerSegmentation

Our Mission:At Avisia, we engage in 100% data-driven projects that blend technical and operational dimensions. Depending on your profile and interests, you will have the chance to work on projects that tackle purely technical challenges or more business-oriented issues.Our clients span a range of diverse sectors including Luxury, Retail, Telecommunications, Banking, and Insurance. You will encounter a variety of data science themes in your projects.Here are some current project examples:Designing models to forecast sales generated on an e-commerce platform for a retailer. #ForecastingDeveloping and industrializing a recommendation engine aimed at optimizing conversion rates for website visitors. #RecommendationCreating an attrition score to identify slowly declining customers for a major retail company. #ChurnImplementing customer segmentation to enhance marketing and sales actions for a brand (targeting, retention, based on channel preferences). #CustomerSegmentation

meilleurtaux is looking for an Experienced Data Scientist / AI Engineer to join the Paris office. The focus is on applying data science and AI skills to real-world challenges, aiming to make a direct impact on customer experiences by transforming data into useful insights. Main responsibilities Collaborate with team members to design and improve AI-powered tools that address business needs Examine data sets to identify patterns, trends, and opportunities that can benefit the company Contribute to projects that use analytics to enhance how customers interact with meilleurtaux’s services Location This position is located in Paris.

About UsAt Ankorstore, we empower independent brands and retailers to flourish by simplifying, accelerating, and enhancing the profitability of wholesale transactions.We are constructing the infrastructure that drives modern wholesale for brands—facilitating their discovery by the right retailers, streamlining ordering processes, logistics, and financing—enabling both parties to collaborate under more sustainable conditions.As a Senior Analytics Engineer, you will play a crucial role in enabling Ankorstore’s teams to make informed, data-driven decisions by designing, developing, and maintaining high-quality analytical data models.You will collaborate closely with internal customer teams (Product, Engineering, Finance & Operations) to identify their analytical requirements, prioritize initiatives, and deliver reliable data assets that support both daily decision-making and long-term strategic initiatives.You will be part of a dedicated team consisting of a Platform Lead, a Data Engineer, and three Analytics Engineers.

Labelium seeks a Lead Analytics Engineer to drive its analytics initiatives in Paris. This role plays a central part in shaping how the company uses data to support decisions across the organization. Key responsibilities Oversee analytics projects from initial design through to full implementation Collaborate with teams across the business to deliver advanced analytics solutions Ensure that strategies and recommendations are grounded in strong data insights Location This position is based in Paris.

Join Polar Analytics: The Premier Data Platform for Consumer Brands ‍At Polar Analytics, we transform complex data into actionable insights, empowering brands to make informed decisions swiftly and efficiently. Our platform is powerful yet accessible, providing DTC brands with the analytics they need to achieve scalable profitability. Our mission is clear: we aim to accelerate the growth of independent DTC brands—enabling them to compete effectively and profitably.Why Choose Polar Analytics? 4,000+ Brands and CountingWe’ve expanded to over 4,000 active merchants as of January 2025, with plans to reach 10,000+ within this year. Revolutionizing AnalyticsPolar is redefining the Shopify analytics landscape through innovative data infrastructure designed for seamless orchestration—placing us at the leading edge of AI-powered commerce automation. Supported by Top-Tier InvestorsWe have successfully raised $28.5M from prestigious investors like Frst, Point9, and Chalfen Ventures, recognized for identifying future industry leaders early. A Team of eCommerce & Data InnovatorsOur diverse team comprises seasoned professionals from leading eCommerce SaaS platforms and Silicon Valley data powerhouses, all united by a common goal: to forge the next industry leader.About UsWe are developing a cutting-edge data & AI operating system tailored for eCommerce—think of it as Datadog for retail.Our work involves processing and refining complex Shopify, advertising, and retention data, making it reliable and actionable for teams.We are seeking engineers who desire real ownership and impact.Your RoleIn this role, you will be engaged with core systems including data pipelines, semantic layers, AI evaluation, and experimentation tools that are vital for thousands of merchants daily.This is not a conventional ticket-taking position. You will:Take ownership of challenges from design through to productionSolve complex infrastructure issues (handling petabytes of data, near real-time processing, and high reliability)

Join Nexton as a Data Scientist specializing in Dataiku and drive innovative data solutions for our clients in the banking and insurance sectors. In this role, you will leverage your analytical skills to extract insights and develop predictive models that enhance decision-making processes.

Quick Overview: In this role, you'll be at the forefront of AI development, training and refining vision-language models, extending their capabilities to video, creating alignment pipelines, developing evaluation benchmarks, optimizing production inference, and engaging with MoE architectures.About UsWhite Circle is a pioneering AI Safety organization dedicated to building a robust safety, reliability, and optimization framework for AI systems. Our platform operates on straightforward natural-language policies that dictate the appropriate behaviors of AI models. We automate the testing, enforcement, and ongoing enhancement of these policies at scale.We have successfully raised $11 million from prominent investors, including founders and senior leaders from OpenAI, Anthropic, HuggingFace, Mistral, DeepMind, Datadog, Sentry, and more.Our infrastructure processes over 100 million API calls every month.We specialize in fine-tuning and training our proprietary LLMs to ensure faster and more cost-efficient performance than any available open or proprietary models.We are a compact, highly motivated team. If you are eager to tackle challenging problems, get your work deployed rapidly, and significantly impact the construction of AI safety – we want to hear from you.Your Responsibilities:Train vision-language models from the ground up and fine-tune existing architectures for advanced image understanding.Expand VLM capabilities to video by designing innovative temporal modeling approaches and efficiently managing long-context.Develop impactful evaluation benchmarks focusing on visual QA, spatial reasoning, and video comprehension.Curate and maintain multimodal datasets, including creating synthetic data generation pipelines.Train and optimize MoE architectures to enhance multimodal inference efficiency.Deploy models into production, focusing on quantization, batching strategies, and latency optimization.You Will Excel If You Have:3+ years of experience in training and fine-tuning vision-language models (e.g., LLaVA, Qwen-VL, InternVL).A strong background in multimodal architectures, with a clear understanding of how vision encoders, projectors, and LLMs integrate.Hands-on experience with RLHF/alignment for multimodal systems, specifically GRPO, DPO, and reward modeling.Experience in video understanding, including temporal modeling and efficient attention mechanisms.

Note: This position is based in Paris, France - relocation support is available for candidates within the EU. Join Trade Republic, Europe’s leading savings platform, where we empower over 10 million customers across 17 countries to grow their wealth through easy, safe, and free access to financial markets. We are on a mission to democratize wealth and help everyone build a prosperous future. By joining our talented team, you will have the chance to leverage cutting-edge technology and contribute to meaningful change for millions. Key Responsibilities: Collaborate closely with product and business teams to establish and develop impactful product metrics. Create analytical products, including data models, dashboards, and reports, to facilitate self-service reporting and analysis. Enhance our data architecture using Snowflake and dbt, focusing on cost efficiency and performance improvements while adhering to best engineering practices. Own projects end-to-end, from planning through execution and adoption, working independently. Ideal Candidate: Minimum of 5 years of engineering experience with a focus on analytics. Deep understanding of architectural design principles and engineering best practices. Proficient in all aspects of the data pipeline: ingestion, transformation, and mart creation. Familiarity with our tech stack is advantageous: S3, Snowflake, Airflow, Python, and dbt. Why You Should Apply: We foster a culture of ownership, excellence, and high energy. We are committed to achieving results and holding each other accountable as we tackle one of Europe’s significant challenges: closing the pension gap and democratizing wealth. If this excites you, we encourage you to reach out!

Our Mission:At Avisia, we engage with our clients on data-driven projects that seamlessly blend technical and operational dimensions. Depending on your profile and interests, you will have the opportunity to work on projects that address purely technical challenges or more business-oriented issues.Our clientele spans a wide array of industries including Luxury, Retail, Telecommunications, Banking, and Insurance. The data science missions you might be involved in are equally diverse.Here are a few current project examples: Designing revenue forecasting models for an e-commerce retailer. #ForecastingCreating and industrializing a recommendation engine aimed at optimizing visitor conversion rates on a website. #RecommendationDeveloping an attrition score to identify slowly declining customers for a major retailer. #ChurnImplementing customer segmentation to enhance marketing and sales strategies based on channel preferences. #CustomerSegmentation

Paris | Full-time | Fluent & As e-commerce continues to flourish, independent brands face challenges in matching the logistics efficiency of giants like Amazon. At Bigblue, we are dedicated to transforming this landscape.We empower brands by democratizing top-tier operations, enabling them to scale faster while providing a five-star customer experience.Since our inception in 2018, we have developed a tech-driven logistics platform that supports over 500 brands, ranging from dynamic DTC players to globally recognized names like MUJI, Aigle, and Cabaïa. With a growing team of 110+ employees across Paris, Madrid, and London, our proprietary Warehouse Management System (WMS) Atlas and our network of 7 warehouses throughout Europe allow us to tackle logistics challenges that others shy away from — making fulfillment faster, smarter, and more sustainable.Supported by over $20M in funding and trusted by the next generation of e-commerce leaders, we are rapidly expanding — aiming for 10 million orders in 2024 as we set our sights on ambitious enterprise growth. We seek a dedicated partner to help us navigate this bold journey ahead.The Role of Data at BigblueAt Bigblue, we are fundamentally data-driven. Data informs our decision-making processes at every level. Our unique position at the heart of our merchants’ operations, combined with our close connection to our fulfillment network, gives us access to vast amounts of fresh, real-time data. This data not only reveals how our merchants are performing but also highlights how we can support their growth. As our network expands geographically, we encounter new data challenges, prompting us to further increase our data team in 2025.Key ResponsibilitiesAddress Customer Data ChallengesAs an integral member of the data practice within the Bigblue product team, you will tackle crucial challenges for our business and our merchants. Your role will involve engaging in product development cycles, focusing on data-related issues while collaborating with designers, engineers, and stakeholders both within and outside of Bigblue. You will oversee the entire problem-solution-experimentation lifecycle, from building proof of concepts to rapidly launching features and experiments to achieve strategic objectives. Your solutions may include data analysis, algorithm development, and machine learning models.Potential projects may include:• Developing a reliable, real-time delivery ETA for buyers,• Enhancing our internal logistics algorithms to optimize specific operational facets...

Nūmi is an innovative bioproduction platform utilizing human mammary cells to create essential ingredients with scientifically validated health benefits throughout all stages of life. Specifically, we are the pioneering European cultivated breast milk company, focused on generating human milk components that closely align with optimal nutrition for infants! As a dynamic early-stage startup, we are on a mission to transform how we nourish the next generation. If you're looking to be part of a rapidly growing, venture capital-backed biotech startup, Nūmi could be your next great opportunity!Situated in the heart of Paris (Hôpital Cochin, Paris 14), Nūmi is supported by esteemed international investors, leading scientists, and prominent academic institutions.Our Culture & Values Positivity: We foster a positive environment at Nūmi, where our mission encourages passionate and energetic communication, always keeping our larger impact in focus. We celebrate small victories but remain committed to our ultimate goals.Excellence: At Nūmi, we define excellence through dedication and a continuous improvement mindset. We view challenges as opportunities to learn and strive for high-quality outcomes. Our growth is driven by effort, attention to detail, and integrity, both as individuals and as a team.Teamwork and Pedagogy: We believe that collaboration strengthens us at Nūmi. We promote knowledge sharing, constructive feedback, and mutual respect, ensuring that every team member contributes to our collective success.Ambition: We set bold goals and encourage expansive thinking at Nūmi. Driven by innovative ideas and determination, we aim high to create meaningful change.Why This Role MattersIn our work at Nūmi, the capacity to identify “golden” cell lines, batches, and conditions relies heavily on our ability to effectively collect, organize, and leverage our data, rather than merely increasing the volume of experiments.Currently, our experimental data encompasses:Electronic Lab Notebook (ELN) entriesSpreadsheetsBioreactor and equipment outputsAnalytical and Quality Control (QC) readoutsThis position is essential for transforming our fragmented data landscape into a cohesive, reliable, and actionable data layer that empowers R&D, informs scale-up decisions, and supports regulatory and industrialization initiatives.As a Lead Data Scientist, you will be a pivotal contributor to advancing scientific progress at Nūmi.Your ResponsibilitiesEstablish Nūmi’s Scientific Data InfrastructureOversee the development of scalable data models and ontologies that accurately reflect experimental workflows, metadata standards, and the scientific landscape.Facilitate the harmonization and integration of data across ELNs, spreadsheets, instruments, assays, and analytical systems into a centralized, user-friendly platform.

Join Vusion Group SA as an Analytics Engineer and play a pivotal role in transforming data into actionable insights. In this full-time position based in Paris, you will collaborate with our R&D department to design and implement robust analytics solutions. Your expertise will help shape data strategies that drive decision-making and enhance our product offerings.

UpSlide est la première solution de productivité et de branding dédiée aux services financiers. Notre logiciel révolutionne l'utilisation de PowerPoint, Word, Excel et Power BI, permettant à des entreprises telles que Citi, KPMG et BNP Paribas de se concentrer sur des activités à forte valeur ajoutée au lieu de perdre du temps sur le formatage ou le copier-coller. Nous sommes en forte croissance, avec environ 200 talents dans nos bureaux à Paris (siège social), Londres, New York, Singapour et Berlin.Nos valeurs Nos valeurs fondamentales orientent notre méthode de travail et sont au cœur de notre processus de recrutement. Pour rejoindre notre équipe, nous recherchons des individus qui partagent les valeurs suivantes :Excellence : Chaque détail compte, et nous veillons à la qualité de nos livrables.Confiance : Nous sommes passionnés, engagés, et nous agissons avec autonomie.Bien-être au travail : Nous cultivons un esprit positif et partageons notre enthousiasme avec nos collègues et clients.Missions et responsabilités En tant qu'Ingénieur en Analytics, tu es responsable de la conception et de la maintenance des produits de données qui facilitent la prise de décision et l'optimisation des performances chez UpSlide. Tes responsabilités incluent :Gérer des projets de données de A à Z : cadrage avec les équipes métiers, développement, livraison et amélioration continue.Construire et maintenir des pipelines de données et des transformations sur Microsoft Fabric avec dbt.Concevoir des tableaux de bord Power BI clairs et exploitables pour suivre la performance commerciale et produit.Collaborer avec les équipes RevOps, Success et Product : qualifier les besoins et challenger les priorités de manière autonome.Notre stack techniqueLangages : SQL, Python, etc.

Join Skello as an Analytics Engineer, where you will play a crucial role in transforming data into actionable insights. Your expertise will help shape data-driven decision-making across the organization. You will work collaboratively with cross-functional teams to develop and maintain data pipelines, ensuring the accuracy and accessibility of data.