Data Science Intern (FT Potential)

finmid

ABOUT FINMID At finmid, we're building infrastructure that integrates access to capital for SMEs directly into the platforms they use daily. We leverage technology, data, and strategic partnerships to deliver financing solutions that significantly outperform traditional financial services, offering SMEs faster, simpler, and more transparent access to funding. As we expand across Europe, the volume and complexity of our contracting grows in parallel: platform partnerships, borrower agreements, supplier procurement, and the regulatory wrapping that holds them together. Our stack combines regulated financial infrastructure with modern software engineering. Legal sits inside that stack rather than adjacent to it. This role is where commercial contracting, product enablement, and AI-driven workflow design meet. THE ROLE Build the commercial legal infrastructure that lets finmid contract at the speed its product ships. You'll be the main legal point of contact for our commercial and product teams, the operator behind every platform, borrower, and supplier contract, and the architect of the systems that make this work repeatable. The goal: a contracting function that scales with revenue rather than with headcount. You'll do this in close partnership with the General Counsel, the Head of Commercial, and product leads across Europe. You'll have a lot of autonomy, but you won't be on your own. This is a deeply cross-functional role and you'll be embedded with the people building, selling, and integrating the product. The problems you'll work on don't have established playbooks yet. You'll need intellectual range: the ability to move between regulatory text, contract drafting, workflow design, and AI tooling without losing the thread. What You Will Work On * Commercial Contracting: Own finmid's contract stack end-to-end across platform-facing, borrower-facing, and supplier-facing agreements. Negotiate independently with counterparties once you've internalised our positions, redline against playbook, and bring back the genuinely hard calls for collective decision. The expectation isn't speed for its own sake. It's quality at volume, with the reasoning legible to anyone who needs to follow it. * Product Enablement: Sit alongside product leads as new features take shape. Translate roadmap into legal frameworks: term sheets, customer-facing T&Cs, partner schedules, and the contractual scaffolding that lets a feature ship without rewriting the agreement every time a parameter changes. Design contracts that flex with the product rather than constrain it. * Contract Management Infrastructure: Build the operating system for commercial legal at finmid. That means a redline review workflow that runs on AI assistance from first pass to negotiation, a clause library and playbook that update themselves as our positions evolve, automated propagation of T&C changes across jurisdictions and languages, version control that nobody has to babysit, and an internal knowledge layer that lets the next hire onboard in days rather than months. * Procurement and Vendor Contracting: Run the negotiation of third-party supplier agreements, from cloud and data providers through to outsourced services. Hold the line on liability, IP, data, and exit terms, and make sure every vendor contract maps cleanly to the regulatory obligations it triggers downstream. * Regulatory-Embedded Contracting: Make sure our commercial paper does the work our regulators expect of it. That includes DORA-grade resilience and ICT third-party requirements, GDPR and sub-processor architecture, outsourcing rules under EU and national supervisory regimes, and vendor risk standards that survive audit. Treat regulatory clauses as reusable components, not bespoke prose. * AI and Tooling: Choose the stack. Claude, Noxtua, Legora, or whatever lands next. Run real experiments, switch off what doesn't work, and integrate what does into daily practice. The remit isn't to tinker. It's to compound leverage: every hour spent on tooling should return many hours of throughput across the team. What Your First 3 Months Will Look Like * Map finmid's full contract surface end-to-end. Identify where contracts collide, where standards drift across products and jurisdictions, and where manual work is silently absorbing your future capacity. * Take over negotiation of at least one live commercial deal and one live procurement contract. Build your reference points by working the actual files, not by reading the archive. * Stand up the first version of a playbook covering our top recurring positions. Make it readable, machine-friendly, and obviously useful to a non-lawyer reviewer. * Get rid of at least one painful manual workflow and replace it with something that runs itself. Pick the candidate (redline triage, T&C version propagation, translation management) that's bleeding the most time and fix it. * Get fluent with the AI tools the team is testing (Claude, Codex, Noxtua and the rest) so they're part of how you work, not something you're still evaluating. * Come back to the team with a 12-month view of what the commercial legal function needs to become, and a clear opinion on sequencing. WHAT YOU NEED TO BE SUCCESSFUL (REQUIREMENTS) Education & Experience * Graduate of a top-tier EU, UK, or US law school, qualified or qualifying in a relevant jurisdiction. * At least one year of experience in Big Law or in-house at a technology company, fintech, SaaS business, or financial institution. The shape of the experience matters more than the count of years. * Direct exposure to commercial contract drafting and negotiation. You should be able to walk into a redline conversation and hold your ground on the substance. * Bonus if you've worked on finance, regulated product, or any setting where commercial contracting has had to coexist with supervisory expectation. Capabilities * You think in systems. When you see a recurring contract problem, your instinct is to design a workflow that prevents it rather than to draft around it case by case. * You think algorithmically. You can decompose a contracting process into decision trees, branching logic, and checkpoints, and you can explain that structure to a product manager or an engineer without translation loss. * You treat contracts as product. You understand that a well-designed agreement is a reusable component, that clause libraries are infrastructure, and that the difference between a function handling 50 deals a quarter and one handling 500 is almost entirely a question of process design. * You're practically curious about AI tooling and willing to get hands-on. In time, you'll develop a clear-eyed view of where current legal AI genuinely accelerates the work and where it quietly creates new failure modes. * You hold the line on legal precision while staying commercially pragmatic. You know which positions are worth fighting for and which are tax on the deal. * You write with precision: clauses, playbooks, internal guidance, and product specs that are unambiguous, implementation-ready, and short enough that someone will actually read them. * You're comfortable working cross-functionally with product and engineering. You don't need to write code, but you should feel at home in a Linear ticket, a design review, or a roadmap conversation. * You enjoy building from scratch. The state of the function on day one should look to you like an opportunity rather than a deficit. * All the while, you maintain a high standard of quality across your outputs and are a trusted advisor to your internal counterparts. BENEFITS * Early commercial legal role with direct access to product, engineering, commercial, and the General Counsel across multiple European jurisdictions, with unusually broad exposure to how a regulated financial product is actually built, sold, and contracted, rather than one narrow slice of it. * We see ourselves as “distributed first” (i.e. work from anywhere) but also have a beautiful office in Berlin where you can work. * We are flexible and cover whatever you need to be as productive as possible. * Home office stipend. * 30 days time off. * Meaningful equity. * Open-minded and transparent culture that includes regular get-together meetings (e.g. All Hands, Brown Bag Lunch, Offsites) We're looking for people with passion, grit and integrity. You're encouraged to apply even if your experience doesn't precisely match the job description. We welcome diverse perspectives and people who think out of the box and aren't afraid to challenge assumptions. Join us.

Artefact

JOIN EFFIXIS, AN ARTEFACT COMPANY: SHAPE THE FUTURE OF GENERATIVE AI AND LARGE LANGUAGE MODELS (LLMS) Are you passionate about generative AI and excited by the potential of Large Language Models ? Effixis, an Artefact company, is seeking an LLM Engineer Intern to join our innovative team. If you've already explored the world of LLMs or have a strong interest in generative AI, this is your chance to contribute to cutting-edge projects and gain hands-on experience in a dynamic, forward-thinking environment. WHO YOU ARE * A student or recent graduate with experience experimenting with LLMs or a strong interest in generative AI and NLP. * Enthusiastic about applying theoretical knowledge to real-world challenges in AI. * Able to thrive in both collaborative and independent projects. * Eager to learn, adapt, and grow in a fast-paced, innovative setting. WHO WE ARE Effixis is part of the Artefact Group, a leading Data & AI consulting firm operating at the forefront of NLP and LLM-driven innovation. With offices worldwide, we help clients across industries, including public health, manufacturing, and media, harness the power of generative AI. At Artefact, we value innovation, collaboration, and continuous learning, and we are committed to fostering an inclusive and supportive workplace. WHAT YOU WILL DO * Collaborate with our data science team to experiment with LLMs and explore innovative generative AI use cases. * Contribute to the development and optimization of NLP and LLM-powered tools and products. * Assist in deploying and maintaining AI systems, including models, APIs, and related infrastructure. * Participate in brainstorming sessions and technical decision-making to shape cutting-edge solutions. WHAT YOU BRING * Hands-on experience with LLMs or a strong interest in generative AI. * Currently pursuing or holding a degree in computer science, mathematics, physics, or a related field. * Familiarity with Python and a willingness to learn NLP and AI frameworks (e.g., Hugging Face, OpenAI, Cohere). * Strong analytical and problem-solving skills. * Good communication skills in English or French (other languages are a plus). WHAT WE OFFER * Competitive internship compensation. * A chance to work with state-of-the-art LLM technology and contribute to groundbreaking projects. * A dynamic, supportive work environment that values creativity and professional growth. * Dedicated resources for training and development. This position is based in Brussels. Don’t worry if you don’t meet all the criteria! We value motivation and potential above all else. We’d love to hear from you and learn more about your passion for generative AI.

Melotech

WHO WE ARE Melotech is revolutionizing media and entertainment. We create art through technology for humans to enjoy. In just 24 months, our work has been heard, watched and loved for over 3 billion minutes worldwide. Founded by entrepreneur and investor Soheil Mirpour, we are backed by top VCs Cherry Ventures, Speedinvest and GFC, alongside world-class angels from firms such as Spotify, Blackstone and KKR. WHAT YOU WILL DO Join us as Data Scientist Intern to bring order to the chaos of culture. You'll extract insights from hard-to-reach data sources to tackle the big questions: What cultural trends are emerging that everyone else is missing? How can we predict virality? And what factors characterize an underserved category? Working fully autonomously alongside our founder and the team, your answers to these questions will directly influence our company's success. On a typical day, your tasks may include: * Discovering and exploiting new, untapped data sources through creative scraping techniques * Building data processing pipelines from scratch to handle raw, unstructured data * Using LLMs and agentic coding tools to accelerate data cleaning and analysis workflows * Spinning up EC2 instances for real-time data collection and automated scraping operations * Prototyping and deploying ML models on AWS for real-time predictions and content analysis * Creating custom dashboards and reports to communicate insights to leadership * Analyzing trends, audience behavior, and performance metrics to guide business decisions WHO YOU ARE We look for upcoming Data Scientists who understand that real impact comes from turning messy, unstructured data into business-critical insights that drive company direction. You're someone who doesn't just build models, you solve complex business problems by finding creative ways to access hard-to-reach data and translate statistical findings into actionable strategies. Typically, your profile will look like this: * Pursuing degree in Data Science, Statistics, CS, Physics, Math, or related quantitative/technical field * Hands-on data science experience in fast-paced business environments across Tier 1 consultancies, Big Tech companies, high-growth start-ups and scale-ups, or media industry leaders * Expert-level Python proficiency with standard data science and ML frameworks * Experience scraping and acquiring raw data from new sources, building creative solutions to access hard-to-reach datasets beyond standard APIs * Extensive hands-on experience with agentic coding tools and LLMs for data workflows * Production model deployment experience including infrastructure and monitoring * Advanced data visualization skills using standard libraries or Tableau * Strong collaboration skills across engineering, product, and business teams * You thrive in a fast-paced and performance-oriented environment * Colleagues would describe you as hard-working, ambitious and persistent * You’re obsessed with music, video or social media WHAT MAKES THIS EXCITING You are one of the first employees of an ambitious team, changing the world of media and entertainment. Being early means every decision you make shapes our trajectory. You're not a cog in the machine but the captain of your own ship, rewarded for performance and respected for leadership. Flat hierarchies mean that your voice matters, your ideas get implemented, and your impact is immediate. We pay competitive salaries and make you an owner of the business with equity. We work remotely to give you complete freedom over your life, while meeting regularly around the world for global offsites where we strategize, bond, and push boundaries together. WHAT THE PROCESS WILL LOOK LIKE We hire on a rolling basis. The earliest starting date is always ASAP. Once you begin our process, you can progress from start to offer within a week, depending on how quickly you can move through each stage: 1. Online assessment: Motivational questionnaire and aptitude test - are you made for the job? 2. Initial interview: 30-minute introductory call - getting to know you 3. Take-home case study: Real-world project - showcase your skills and working style 4. Case interview: 90-minute case discussion - present and debate your results with a team member 5. Founder interview: 90-minute interview with our CEO - going deep on all topics 6. Team interview: Individual or group interview with other team members - depending on position 7. Offer, contract signing and onboarding Note: As we are still in stealth, you will learn more about Melotech as you progress through the stages. By the end of the Founder interview, you will have a full grasp of our business and the details of your role.