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Senior Analytics Engineer / Semantic Model Owner (Microsoft Fabric / Power BI)

QBI Solutions

YOUR MISSION We are looking for a Senior Analytics Engineer / Semantic Model Owner (Microsoft Fabric / Power BI) to help build and govern QBi’s next-generation analytics foundation. This is not a report-factory role. The role exists to reduce one-off reporting effort by building reusable, governed and scalable data products: Microsoft Fabric data structures, Power BI semantic models, KPI definitions, validation rules, reporting patterns and renewable-domain data models that can be reused across customers, internal teams and future product modules. The ideal candidate combines strong data modeling and Microsoft Fabric capability with data-quality discipline and the ability to translate industry-standard workflows into robust analytical structures. This person should be comfortable working with business stakeholders, product teams, data engineers, analysts and leadership. They must be able to distinguish between a one-off dashboard request and a recurring data-model need that should become part of QBi’s reusable data foundation. Mission Your mission will be to turn QBi’s renewable-energy knowledge into scalable data and semantic-model assets. You will be instrumental in showing how and helping QBi move from fragmented reporting and ad hoc BI execution toward a governed analytics layer that supports: * Existing customer reporting and reporting modernization;  * Microsoft Fabric / Power BI semantic-model governance;  * Technical Analytics and data-quality logic;  * Data Model-as-Infrastructure / Renewable Data Foundation offers;  * Future AI-native product and operational workflows;  * Future Revenue Copilot and hybrid revenue intelligence products.  WHAT THIS ROLE IS — AND IS NOT This role IS * a senior analytics engineering role;  * a semantic model ownership role;  * a Microsoft Fabric / Power BI governance role;  * a renewable-domain data-model role;  * a bridge between business needs, data structures and scalable analytics;  * a role that uses AI to accelerate analytics engineering, documentation and model review.  This role IS NOT * a generic Power BI report-builder role;  * an open-ended “stakeholder asks, we build a dashboard” role;  * a data-science key trends informed role;  * a deep ML engineering role;  * a generic Microsoft consulting role;  * a role that accepts unbounded custom work without converting it into reusable patterns.  Key Interfaces This role will work closely with: * Data Engineering;  * BI / Reporting;  * Product Builders;  * Architecture / Platform;  * selected external Fabric or data-platform specialists where needed.  And from time to time with: * Customer Operations and Professional Services;  * Commercial / KAM teams;  * future Revenue Copilot and Renewable Data Foundation owners;  KEY RESPONSIBILITIES 1. Own and evolve QBi’s semantic model layer * Design, maintain and improve reusable semantic models for Power BI and Microsoft Fabric.  * Define consistent KPI logic, measures, dimensions, hierarchies and analytical relationships.  * Maintain metric definitions, calculation logic and semantic-model documentation.  * Ensure business users, analysts and AI tools work from trusted semantic foundations.  * Review changes to key measures, shared datasets and customer-facing analytical structures.  2. Build scalable data models in Microsoft Fabric * Design conceptual, logical and physical data models for renewable-energy use cases.  * Work with Microsoft Fabric Lakehouse, Warehouse, semantic models and related data-engineering patterns.  * Translate renewable asset, portfolio, contract, event, revenue, reporting and data-quality concepts into scalable model structures.  * Collaborate with data engineers on ingestion, transformation and validation patterns.  * Support reusable Fabric architectures for internal and customer-facing use cases.  3. Reduce custom BI workload through reusable analytics assets * Convert recurring reporting needs into reusable semantic models, templates, report families and governed data products.  * Challenge ad hoc report requests when the better answer is model improvement, template creation or self-service enablement.  * Build reporting structures that reduce manual BI customization.  * Help define which requests become product features, governed analytics patterns or bounded expert-service work.  4. Strengthen data quality, governance and trust * Define validation rules, reconciliation checks, data-quality indicators and confidence signals.  * Classify and explain data-quality issues in operational and customer-facing contexts.  * Support lineage, data ownership, metric governance and semantic-model change control.  * Identify where data-quality limitations affect reporting, customer trust or product behavior.  * Ensure analytical outputs are explainable and defensible.  5. Support QBi’s Renewable Data Foundation strategy * Turn QBi’s renewable-data knowledge into reusable data-model assets.  * Create renewable-domain object dictionaries, data-domain maps, semantic patterns and implementation templates.  * Contribute to Microsoft Fabric-based customer enablement offers.  * Protect QBi’s model quality and IP boundaries by avoiding unstructured bespoke consulting.  * Build repeatable methods and standards rather than one-off customer-specific solutions.  6. Support future product modules and AI-enabled analytics * Support future product surfaces around AI-assisted operational workflows.  * Provide the semantic and analytical structures needed for AI-assisted explanation, reporting, recommendations and user-facing analytics.  * Use AI tools to accelerate documentation, SQL/DAX scaffolding, semantic-model review, data-quality analysis and report prototyping.  * Ensure AI-generated analytics remain grounded in governed models and reviewed logic.  7. Engage with business stakeholders without becoming a request queue * Gather and clarify business requirements directly from stakeholders.  * Translate business questions into reusable data-model, semantic-model or reporting needs.  * Push back constructively when requests are unclear or better solved through existing models.  * Explain data-model decisions in business language.  * Clarify what can be self-served, what needs governed modeling, and what should become a product or platform capability. YOUR PROFILE Required Experience * Senior-level experience in analytics engineering, semantic modeling, BI engineering, data modeling or a closely related role.  * Strong practical knowledge of dimensional modeling, star schemas, snowflake schemas and analytical model design.  * Hands-on experience with Microsoft Fabric or the Azure data stack, with a clear willingness and ability to work deeply in Fabric.  * Strong Power BI semantic-model experience, including measures, model relationships, performance considerations and governance.  * Strong SQL and data-warehouse / lakehouse understanding.  * Experience translating business requirements into scalable analytical structures.  * Ability to communicate clearly with both technical and non-technical stakeholders.  * Strong data-quality mindset: validation, reconciliation, lineage, consistency and trust.  * Ability to work autonomously while collaborating closely with Data, Product, Engineering, Customer Operations and Commercial teams.  Required Working Style * You think in models, not only reports.  * You prefer reusable data assets over one-off dashboards.  * You can challenge business requests without blocking business outcomes.  * You document and govern what you build.  * You are comfortable working in a company that is changing its operating model.  * You use AI to accelerate work, but you do not treat AI output as automatically correct.  * You can operate in ambiguity, but you do not leave ambiguity undocumented.  Strong Plus * Experience in renewable energy, energy markets, asset management, infrastructure, utilities or industrial analytics.  * Experience with SCADA, telemetry, asset-performance data, energy-settlement data or operational event data.  * Experience with Microsoft Fabric certification paths or Microsoft data-platform governance.  * Experience designing KPI dictionaries, semantic-layer governance or enterprise BI standards.  * Experience using AI assistants or copilots for analytics engineering, documentation, SQL/DAX support, model review or reporting acceleration.  * Familiarity with data-product thinking.  * Familiarity with data governance, data contracts, CI/CD for analytics, or semantic-model lifecycle management.  AI Expectations This role does not require deep machine-learning research expertise. It does require an AI-enabled working style. The successful candidate should be able to use AI tools to: * accelerate SQL and DAX drafting;  * document models and measures;  * summarize data-model logic for business users;  * generate first-pass validation checklists;  * scaffold report concepts;  * identify potential metric inconsistencies;  * support internal knowledge-base creation.  However, the candidate must also understand that AI sits above governed semantic models. It must not replace metric governance, data validation, security review or human judgment. Renewable Domain Learning Expectations Prior renewable-energy experience is valuable but not mandatory if the candidate shows strong abstraction ability and learning discipline. WHAT ‘GOOD’ LOOKS LIKE Success in the First 90 Days By the end of the first 90 days, the successful candidate should have: * mapped QBi’s current Fabric / Power BI / semantic-model maturity;  * identified the most important duplicated or fragile reporting structures;  * produced a first semantic-model governance baseline;  * documented the key reusable data domains and priority KPI families;  * proposed a target Fabric / semantic-model architecture for the highest-priority use cases;  * defined a practical backlog for reporting modernization and model consolidation;  * reduced at least one recurring reporting pain point through a reusable model or template;  * created clear rules for what should be built as custom BI versus governed reusable analytics;  * established a working relationship with Product, Data, Customer Operations and Commercial stakeholders.  Success After 6–12 Months Success after 6–12 months means: * QBi has a clearer, governed semantic-model backbone;  * Power BI and Fabric work is less dependent on scattered individual knowledge;  * recurring reporting requests are increasingly served through reusable models and templates;  * data-quality and metric-definition issues are more visible and better controlled;  * the company has stronger foundations for Data model-as-Infrastructure offers;  * future product modules can rely on trusted analytical structures;  * AI-assisted analytics work is faster, but still governed and credible.  Are YOU what WE are looking for? The right candidate is not simply someone who can build dashboards. We are looking for someone who sees data modeling as a way to create leverage: someone who can take a complex business problem, uncover the structure behind it, and turn it into a trusted analytical foundation that can be reused across teams, customers and products. This person should combine technical depth with business judgment. They must be able to design robust semantic models, define governance logic, document decisions clearly, and challenge requests when a one-off report is not the right answer. The ideal candidate will be senior enough to push back, structured enough to create order, technical enough to build, and business-facing enough to explain why good data models matter. They should want to help QBi move from fragmented reporting to a scalable, governed analytics foundation for the next stage of the company. Are WE what YOU are looking for? If you want a role where data modeling is treated as a strategic capability, not a reporting support function, QBi may be the right environment for you. This is a transformation role. We are bringing in someone who has already mastered semantic modeling, Microsoft Fabric, Power BI governance and scalable analytics foundations, and who can help guide QBi in how to do this properly. You will help shape the analytical backbone of the next stage of the company: trusted data models, reusable semantic layers, data-quality standards, AI-enabled analytics and renewable-energy domain structures that support products, customers and internal operations. This is not a role built around maintaining dashboards. It is a role for someone who wants ownership, influence and impact. You will work closely with Product, Data, Engineering, Customer Operations and Commercial teams, helping move QBi from fragmented reporting toward a governed, scalable and AI-ready analytics foundation.  If you want your work to define how a company transforms its data capability, this is the kind of role where that can happen. WHY US? What we offer ✅Competitive fixed and variable salary in line with the sector, based on merit and experience. ✅Flexible remuneration (meal vouchers, transportation vouchers, and childcare vouchers). This allows you to optimize your salary thanks to the tax savings it generates. ✅Opportunity for growth in one of the most dynamic, future-proof, and fastest-growing areas: digitalization in the renewable energy business. ✅Work with an incredible team that has created a market-leading product for large companies in the sector. ⭐Lots of creative freedom. ✅Fun is part of our day: we love organizing fun initiatives that help create an even more pleasant internal atmosphere :). ✅Flexible start time with a hybrid model (4 days of home office and 1 day of office work). ✅A prime office location in downtown Madrid. ✅Intensive working time during summer months.  ✅Individual English classes (1 hour a week).

Customer Success Manager

Humaans

ABOUT US Humaans is building the next generation of infrastructure for the workplace; software designed for companies that are scaling fast, operating globally, and pushing into new boundaries. What started as a system of record has evolved into a broader platform for operating people globally. With Athena, our agentic AI layer, Humaans moves beyond data management into intelligent orchestration, connecting workflows across HR, IT, Finance, and Operations so organisations can act faster and with greater confidence, redefining how work gets done. We work with ambitious teams across Europe and the US, from AI-native companies like Lovable, Poolside, Fyxer AI, and Tandem Health, to established, high-growth organisations scaling internationally and through acquisition, including Quantexa, Sellpy, Manychat, Gigs, Croud, and Threecolts. These teams don’t buy software for features,they buy leverage. The ability to run faster, cleaner, and with more control as complexity compounds. To date, we’ve raised $20m in venture funding from some of the most respected founders, operators, and funds in technology: Lachy Groom (Physical Intelligence), Stewart Butterfield (Slack), Tobias Lütke (Shopify), Dylan Field (Figma), Jeff Weiner (LinkedIn), Claire Johnson (Stripe), Oliver Jay (OpenAI), Jay Simmons (Bond) as well as Y Combinator, Moonfire, Frontline Ventures, Pathlight Ventures, and Exor. If you have massive ambition and want to work on a hard problem, with a small team that moves fast, at a moment when the category is genuinely up for grabs - this is it. THE ROLE You'll manage a portfolio of our strategic customers . But this isn't traditional CS, you'll be at the frontier of AI adoption in HR tech. * Own the end-to-end customer relationship for strategic accounts, from onboarding through renewal and expansion * Conduct deep-dive discovery to define customer objectives, requirements, and the operational landscape needed to successfully deploy our solutions. * Guide customers in tailoring and optimising our AI agent capabilities to solve unique operational challenges and maximise end-user resolution rates. * Use AI tools to draft QBR materials, summarise call transcripts, flag account risk signals, and build repeatable assets faster * Proactively analyse performance data to track AI effectiveness, drive continuous improvement, and ensure customers realise measurable value (e.g., deflection, quality, CSAT). * Build and execute success plans that tie platform usage and adoption to measurable business outcomes * Identify and close expansion opportunities across your portfolio, working closely with Sales on new logos * Act as the voice of the customer internally, closely collaborating with Product and Engineering to feed insights back and shape the roadmap * Develop playbooks, frameworks, and best practices for AI-enabled customer success as the function scales * Monitor account health proactively, mitigating churn risk before it materialises WHAT WE'RE LOOKING FOR * 4+ years of experience in Customer Success, Account Management, or a related customer-facing role, ideally in B2B SaaS. If you’ve not worked in customer facing roles but have people ops experience specifically in helping companies to drive AI efficiency, we’d be keen to hear from you. * Customer-Centric: Deeply customer-obsessed, driven by delivering real, measurable business outcomes and value * Genuinely product-centric — you understand how software works, you're curious about what's under the hood, and you can translate technical capability into business value * AI-experienced — Has meaningfully changed how they work using AI, and can walk us through what they built, what broke, and what the outcome was * Commercial instinct — enough CS and commercial experience to navigate enterprise relationships, drive expansion, and have confident commercial conversations * Comfortable with pace and ambiguity — startup experience is a plus; you thrive when the playbook hasn't been written yet * Excellent communication — you can run a room, write clearly, and earn trust quickly with senior stakeholders * High ceiling — we care more about your trajectory and potential than your tenure This is an in-person role. Our team comes together in the office Monday through Thursday, while most of the team collaborates in person on Mondays, Tuesdays, and Thursdays. PACKAGE & BENEFITS Early stage startups can be messy – we know that. We're putting effort in providing you with the best employee experience and a quality driven environment in exchange for trusting us. * Market-leading compensation that reflects your value * 25 days paid time off each year plus public holidays * Share Options with 5-year exercise window so you don’t feel pressure to exercise if you leave * Free Thursday lunches at HQ, quarterly team events, and company offsites. * Top tier private coverage for health, vision and dental care * A new MacBook and tools you need to do your best work * Enhanced parental leave with up to 16 weeks for primary and 4 weeks for secondary * Learning & development budget WHY JOIN HUMAANS TODAY? HR tech is having its AI moment and we’re positioned to own it. Humaans started as a next-gen HRIS taking on large incumbents in a massive market. We’ve since evolved into something even bigger: an AI platform that sits across workforce data and automates the operational layer of HR entirely; the natural progression of what we’ve been building toward. The product is highly differentiated. It’s built around a structured workforce data model that makes AI reliable in an HR context, something no one else has gotten right. Customers notice the difference immediately. We’re backed by Y Combinator, Lachy Groom, Moonfire, Frontline Ventures, and operators who’ve built some of the most consequential software companies of the last decade: the founders of Slack, Figma, and Shopify, and Asana’s former CRO and Head of OpenAI International. We’re a small team with an unapologetically high bar. It shows up in the product, in how we communicate, and in the standards we hold each other to. OUR COMMITMENT TO DIVERSITY At Humaans we’re looking for genuinely good people that are transparent and emphatic. We’re committed to providing equal opportunities, a diverse and inclusive work environment, and ensuring a fair interview process for everyone. You’re welcome to apply no matter your gender, ethnicity, sexual orientation, religion, civil or family status, age, disability, or race. PRIVACY NOTICE We care about your privacy. When you apply for a role at Humaans, we’ll collect and process your personal data as part of our recruitment process. This includes things like your CV, contact details, and any other information you choose to share. We may also contact you about future opportunities. You can ask us to delete your data at any time. For more details, see our Privacy Policy.

Senior Product Engineer (Full Stack)

Ophelos

OUR MISSION At Ophelos, we believe in a different way to deal with debt. One that puts empathy and understanding front and centre, approaching our customers as individuals — no matter what they’re going through. For too long, people in debt have borne the brunt of poor industry practices. Intimidating tactics, time-consuming customer service and a one-size-fits-all approach that overlooks the reasons anyone can fall into debt in the first place. Meanwhile, businesses suffer too. Poor customer experience translates to poor customer satisfaction, high churn rates, bad brand reputation and ultimately missed opportunities. That’s why we’re taking a radically different approach. Pioneering an industry-first AI-native collections platform, we build products that help individuals clear their debts in a way that suits them, whilst providing businesses with an improved customer experience and game-changing insights into their customer base. Since our launch in 2021, we’ve worked with some of the UK’s leading companies, including Octopus, Scottish Power and Philips — helping millions of people move toward a more stable, debt-free future. In 2023, we were acquired by Intrum, Europe’s biggest credit management service and have begun the next phase in our growth — expansion into 17 European markets over the next two years. SENIOR PRODUCT ENGINEER (FULL STACK) We are seeking an enthusiastic and ambitious Senior Product Engineer with a keen eye for quality to join our growing Engineering function. You will be joining our Payments squad, responsible for building out our cross-market flexible Payments capability. This is a team which has recently transitioned to being "LLM-first" in their working style, so you would be joining at a critical moment to shape our ways of working and our approaches to LLM-based tooling. At Ophelos, we don't have traditional product or design functions — our engineers own the full problem, from identifying what needs to be built through to shipping and iterating on it. If you're energised by that kind of end-to-end ownership and want to operate closer to the product than most engineering roles allow, this is the role for you. In this role, you'll get to: * Design, implement and deliver software features with full ownership from start to finish — from problem definition through to production. * Take genuine product ownership: identify user and business needs, define solutions, and make pragmatic trade-offs — not just execute on a brief handed to you. * Have real opinions about how things should be built, and back them up. We want engineers who push back — on a design pattern, a tool choice, or a suggestion from an AI agent — when the second- and third-order consequences don't stack up. * Work in an environment that's largely backend-heavy right now (though that mix will evolve), with the autonomy to shape how it's built. * Collaborate as part of a close & multi-disciplinary team. Your work will have meaningful and measurable impact on our organisation and products. * Own business-critical components and ensure their stability and maintainability — and know how to prove it, through the numbers you track. * Mentor other members of the team to ensure technical excellence and continuously raise the bar when it comes to engineering standards. * Share your ideas with the team and build products that make an incredibly impactful difference to society and people's lives. Ophelos is an AI-first technical organisation and effective use of LLMs is central to how our engineers work. Claude Code and other agentic tools are critical to our toolbox, and we're as interested in engineers who bring their own AI-assisted workflows and habits to the team as we are in engineers who already use ours. The right person for this role is excited by this world, uses it daily in their own work — professionally or personally — and enjoys helping others get better at it too. Stack-wise, we run TypeScript, Python, and Ruby at various levels. For this role we're really seeking a polyglot Software Engineer for whom specific implementation language is not critical. More broadly, our stack includes: * A modern web application framework (we use FastAPI; comparable experience elsewhere is fine) * A relational database layer (we use PostgreSQL) * Workflow orchestration and data infrastructure tooling * AWS and container-based cloud infrastructure * Claude Code for LLM-first software engineering * Datadog for monitoring & observability Ophelos operates hybrid working, and believes face-to-face working time is essential for planning and alignment. Our teams spend three days each week working in-person from our comfortable office near Liverpool Street in London. ABOUT YOU More than anything we are interested in your general experience as a software developer and your approach to solving problems. The ideal candidate thinks like a product owner and builds like an engineer — someone who is energised by ambiguity, comfortable shaping the problem as much as solving it, and who takes personal pride in the real-world impact of what they ship. Some experience in the following is important for this role: * At least 5 years of experience in full stack engineering, with real depth somewhere in your backend work - this role skews backend-heavy today. * Experience with TypeScript, Python, Ruby, or a similarly high-level language, and comfort designing and integrating APIs - particularly in environments where data sensitivity or regulation raises the stakes. * Breadth across problems and systems tends to serve people better here than narrow specialisation in one area - we'd rather hear about the range of things you've owned than the depth of one niche. * You enjoy learning new technologies and are passionate about experimenting to figure out how to build things in a better way. * You're comfortable working from a problem statement rather than a fully specced brief - you can move from ambiguity to a clear technical approach independently, and you actively contribute to shaping what gets built, not just how. * Genuine enthusiasm for using the latest LLM tools — Claude Code, Cursor, Codex or similar — is critical, as is the intent to keep developing your skills as the agentic software engineering landscape evolves. Bonus points if you've helped teammates or a wider team get better at this too. * You don't just ship - you measure. You can point to how you know something you built actually worked, whether that's a business number, a reliability metric, or both. * Attention to detail, intellectual curiosity & a willingness to embrace the changing technical landscape we find ourselves in. * You are excited about Ophelos' mission to support households and businesses to break the vicious debt cycle. Experience in fintech, or in regulated or compliance-heavy environments more broadly, is a genuine bonus - but we've hired brilliant people here without it, so don't rule yourself out if that's not your background. ABOUT OUR TEAM Ophelos launched in June of 2021, backed by investors such as AlbionVC, Connect Ventures and Fly Ventures. In 2023, we were acquired by Intrum, Europe’s biggest credit management service. Our growing team has team helped build some of the world’s most successful businesses, including the likes of Monzo, Google, Oracle, ASAPP, IBM and more — in addition to pioneering innovative products, sitting at the intersection of enterprise, financial technology, artificial intelligence and academia, working with institutions such as Oxford University, the University of Amsterdam and the University of Hong Kong. OUR VALUES Supporting customers and businesses to improve their financial health is a long-term mission. Our company values act as our north star, steering our every move as an organisation and are the backbone of our unique company culture. Our values and culture allow us to stay true to our larger purpose, even as we continue to grow at a rapid pace. Customers and Clients first – We exist to help real people move through debt and to get clients paid back. This commitment drives how we design products, deliver services, and interact with customers and clients daily. Dream big – We have ambition and drive to succeed - we’re not just raising the bar, we’re confidently asserting ourselves as the benchmark. Get it done – We’re decisive and embrace a sense of urgency; we don’t let opportunities get away from us. We’d rather act quickly and take informed risks, iterating and learning as we go.  Win as one - We work as one team, supporting each other and aiming for shared goals. At Ophelos, the team isn’t just individual departments - it’s all of us together.  We challenge and support each other because we care about everyone’s growth and success.  Ophelos is committed to creating a diverse work environment and is proud to be an equal opportunity workplace, providing equal employment and advancement opportunities to all team members. We are building an environment where every Ophelos team member can thrive, feel a sense of belonging, and do the best work of their careers. We value diversity and recruit, hire, and promote individuals solely based on talent, qualifications, competence, and merit. We evaluate candidates without regard to race, colour, religion, age, sex, sexual orientation, gender identity, national origin, disability, or other protected characteristics as required by law and as a matter of our company values. GDPR NOTICE  When you apply to a job on this site, the personal data contained in your application will be collected by Ophelos ("Controller"), located at 1 Finsbury Ave, London EC2M 2PF, and can be contacted by emailing support@ophelos.com. Controller's data protection contact is Kofi Barnes, who can be contacted at support@ophelos.com. This notice explains how we process your personal data throughout our recruitment process, including at the interview stage described below. Applying for a role with Ophelos is subject to the practices described in this notice — it is not a separate agreement you sign, but a description of how the recruitment process works. You won't be given a separate notice at each stage; Ophelos retains discretion over which of the described tools and processes are applied to any given application or interview, within the purposes set out below. This discretion does not extend to introducing automated decision-making without human review — that is addressed separately below. What we use your data for Your personal data will be processed for the purposes of managing Controller's recruitment-related activities, which include reviewing applications, setting up and conducting interviews and tests, evaluating and assessing the results, and as is otherwise needed in the recruitment and hiring process. As part of this process, we use software tools — including AI-assisted tools — to help us organise, screen, and evaluate applications and interviews. This includes: * Automated analysis of CVs and application materials to identify relevant skills and experience * Automated analysis of interview transcripts to help summarise and score responses (see "Interviews" below) * Generating scores, summaries, or insights to assist our recruiters Currently, these AI-assisted outputs are advisory only. A human recruiter reviews every application and every AI-generated score or summary before any decision is made, and no application is filtered out or rejected by an automated process alone. We may in future use automated tools to make, or take part in making, decisions about your application without human review at that stage, if we do so in a way that complies with applicable law at the time — for example, by obtaining your explicit consent, or where the decision is necessary for entering into a contract with you, and in either case only with appropriate safeguards, including your ability to request human review of, and to contest, that decision. If we intend to introduce this, we will update this notice and separately inform you before it applies to your application — this notice alone does not authorise it. We also use historical, aggregated recruitment data to improve our processes generally — for example, to better understand which factors tend to be associated with successful hires. Where this involves data from past applicants, it is anonymised or aggregated before use, and is not used to make any decision about a specific individual. Such processing is legally permissible under Art. 6(1)(f) UK/EU GDPR as necessary for the legitimate interests pursued by the Controller: the solicitation, evaluation, and selection of applicants for employment, and the improvement of Controller's recruitment processes. Interviews — recording and transcription If you're invited to an interview conducted by video or phone call, it will be recorded and automatically transcribed as a standard part of our recruitment process — this is described in this notice, which applies to your application as explained above. Where an interview is recorded: * The interview will be recorded and transcribed using our video-calling provider (Google Meet). * The transcript will be processed by AI tools (including models provided by Anthropic and Google) to help generate a summary and structured notes for the interview panel, and to help train and improve our own recruitment tools as described above. * The recording, transcript, and any AI-generated summary will be stored on Ophelos's systems (hosted via Cloudflare) and in Greenhouse. * A human interviewer/panel always reviews the AI-generated summary as part of forming their own assessment — it is a starting point for the panel, not a decision in itself. Recording and transcribing interviews in this way is necessary for us to evaluate all candidates fairly and consistently, and is carried out under our legitimate interests (Art. 6(1)(f) GDPR) in running a fair, well-documented recruitment process. Who we share your data with Your personal data will be shared with the following processors, engaged by Controller to help manage its recruitment and hiring process: * Greenhouse Software, Inc. — applicant tracking system (United States) * Google LLC — video interview hosting/recording (Google Meet), and AI models used to help analyse application and interview materials (United States) * Anthropic, PBC — AI models used to help analyse and summarise application and interview materials (United States) * Cloudflare, Inc. — infrastructure and data storage supporting our recruitment tools [confirm storage region before publishing] We use application and interview data, including through AI-assisted tools, to train and improve our own internal recruitment tools and models — for example, to refine how we identify relevant skills and experience, and to better understand what tends to be associated with successful hires. This is part of how we evaluate and improve our recruitment process on an ongoing basis. The third-party AI providers who process this data on our behalf do not use it to train their own general-purpose AI models — it is used only to generate the specific outputs described in this notice. International data transfers Because the above providers are located in or transfer data to the United States, if you are located outside the United States, your personal data will be transferred to the United States once you submit it or once your interview is processed. Where the European Commission has not made an adequacy determination covering such a transfer, it is subject to appropriate safeguards, including Standard Contractual Clauses and/or the EU-U.S. Data Privacy Framework where the recipient is certified. You can obtain a copy of the relevant safeguards by contacting support@ophelos.com. How long we keep your data Your personal data, including any interview recordings, transcripts, and AI-generated summaries, will be retained for the duration of the recruitment process and for 24 months afterwards, to allow us to consider you for other roles and manage any related legal claims, after which it will be deleted or anonymised. You can request earlier deletion at any time by contacting support@ophelos.com. Your rights Under the GDPR, you have the right to request access to your personal data, to request that it be rectified or erased, and to request that processing be restricted. You also have the right to data portability and the right to object to processing based on legitimate interests, including interview recording — though for the reasons explained above, we may not be able to progress an application where a candidate objects to standard recording of the interview stage. In addition, you may lodge a complaint with an EU or UK supervisory authority (in the UK, the Information Commissioner's Office).