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Visar 5 av 21 lediga jobb för "Data scientist"
Rensa sökfilterSenior Machine Learning Engineer
On behalf of a partner company, Nordic Investin is looking for a Senior Machine Learning Engineer. You are interested in models that perform after deployment, when data shifts, latency appears and users behave differently than the notebook assumed. The partner is moving machine learning capabilities into core products and workflows. You will develop models and the production systems around them, working with data scientists, platform engineers and product teams. The partner wants data and AI work that can be operated, explained and improved after launch. Provenance, quality, access and evaluation belong in the solution from the beginning. How you will work You will work with engineers, analysts and domain specialists who look at the same information from different angles. The partner expects assumptions, datasets and evaluation methods to be visible. Solutions should be designed for repeatable delivery, monitored use and responsible change after deployment. As a senior colleague, you will own substantial outcomes and help others make stronger decisions. You are expected to recognise risk early, communicate it without drama and move work forward with practical alternatives. The role still includes hands on delivery; seniority here means broader judgement, not distance from the work. What you will do Build and productionise machine learning models in Python. Design feature, training and inference pipelines. Evaluate models against product and operational requirements. Improve monitoring for quality, drift, latency and cost. Create reproducible experimentation and deployment workflows. Guide technical choices between classical ML, deep learning and simpler rules. What you will bring Strong Python and applied machine learning experience. Evidence of deployed models used in a real product or process. Solid software engineering, testing and API development. Experience with cloud compute, containers and data pipelines. Understanding of model evaluation and monitoring. Ability to explain uncertainty and tradeoffs to non specialists. Experience that would add value NLP, computer vision or geospatial modelling. Spark, Databricks or large scale feature processing. Experience in a regulated decision environment. A background that can succeed here Your background may be software engineering, data science, applied research or quantitative analysis. We care that you can connect model performance with production behaviour and user value. What makes the opportunity interesting This is a role for someone who wants ownership beyond training a model. The partner offers meaningful data, strong engineering collaboration and the opportunity to shape how machine learning becomes a dependable product capability. The exact partner, employment model, compensation, start date and working arrangement will be explained openly during the process. Nordic Investin will make sure you understand the context, expectations and decision path before you are asked to commit significant time. The recruitment conversation During the process, Nordic Investin will focus on concrete decisions you have made: the context you received, the alternatives you considered, the result you observed and what you would change today. You do not need every optional technology if your core experience transfers and you can explain how you would close the gap. How to apply Apply with your CV or LinkedIn profile and a short note describing the most relevant system, product or transformation you have helped deliver. Nordic Investin welcomes candidates with different routes into technology and assesses applicants on relevant capability, judgement and potential.
Global Ontology and Semantic Data Leader
About the Role Establish and lead a global ontology and semantic data strategy for the Digital Energy software organization. This role defines how products, systems, devices, points, relationships, behaviors, and operational concepts are represented consistently across the portfolio. This is not a purely theoretical or governance-focused position. The successful candidate will combine deep semantic-technology expertise with the practical engineering ability to build and apply ontologies in real software products. What You Will Do Establish and lead the global ontology and semantic data strategy for DE Software. Define a common approach to semantic modeling, entity relationships, metadata, classifications, and data tagging. Develop practical ontologies for buildings, energy management, automation systems, and related domains. Apply RDF, RDFS, OWL, SHACL, SPARQL, JSON-LD, and knowledge graphs where appropriate. Establish processes for ontology development, versioning, validation, extension, and governance. Create reusable semantic models that can be adopted across multiple products and engineering teams. Translate operational concepts into machine-understandable models with product architects, software teams, data teams, AI teams, and domain experts. Identify opportunities to use semantic models to improve interoperability, analytics, search, engineering efficiency, and AI capabilities. Partner with the applied AI team to provide structured domain knowledge, grounding, and contextual relationships. Develop reference implementations and working prototypes that demonstrate business and technical value. Evaluate existing industry ontologies, taxonomies, schemas, and standards before creating proprietary extensions. Build a global community of practice around ontology and semantic data. What Will Help You Succeed Significant professional experience with ontology engineering, semantic technologies, knowledge graphs, or closely related disciplines. Hands-on experience designing and implementing semantic models in production or product-oriented environments. Strong understanding of RDF, OWL, semantic relationships, controlled vocabularies, taxonomies, and data classification. Experience with data tagging, metadata management, entity modeling, and semantic validation. Ability to explain what an ontology is, why it matters, and how it creates value for software products and customers. Strong software, data engineering, or technical architecture background. Demonstrated ability to influence multiple product and engineering organizations without relying solely on direct authority. Excellent written, verbal, and visual communication skills. Preferred Qualifications Experience in smart buildings, building management systems, industrial automation, energy management, IoT, or digital twins. Experience with Brick Schema, Project Haystack, RealEstateCore, SAREF, BOT, or other relevant industry models. Experience integrating semantic models with operational databases, event systems, APIs, analytics platforms, or AI applications. Experience applying knowledge graphs or ontologies to retrieval-augmented generation, AI grounding, reasoning, or agent-based systems. Experience leading an enterprise-wide semantic architecture or ontology program. Familiarity with graph databases and semantic stores. Leadership Profile Highly articulate and able to create clarity from complex concepts. Pragmatic rather than dogmatic. Comfortable defining a long-term strategy while delivering near-term results. A recognized expert who continues to work directly with technology. Collaborative across product, architecture, engineering, and business teams. Capable of becoming the trusted global authority for ontology within DE Software. What Success Looks Like Publish and align a DE Software ontology strategy. Deliver an initial shared semantic model for a priority domain. Create an ontology governance and versioning process. Achieve adoption by one or more product or platform teams. Demonstrate measurable value through an AI, interoperability, engineering, or analytics use case. Establish a global ontology community of practice. Working in the DE Software CTO Office You will join a highly collaborative, global environment focused on turning emerging technologies into practical software capabilities. These positions require hands-on contributors who can create working implementations, validate ideas through engineering, and partner effectively across product, architecture, domain, and development teams. #LI-HB6 At Schneider, we believe that every employee is a talent who deserves equal opportunities. This means you matter. Every individual needs to feel valued, supported, and treated fairly to do their best work. Our Total Rewards is our way of saying: “We see you. We value you”. It’s more than just pay and benefits – it’s a meaningful investment in you. It is designed for you to perform, grow, feel safe, and elevate your potential to shine as an impact maker. Schneider Electric is there when it matters most to you Our Total Rewards package outlines all the benefits and support you’ll enjoy as part of the Schneider Electric team: Care for Yourself and Your Family. We ensure you feel secure with benefits that help you and your family thrive: important insurances, paid leave, parental and care leave, wellness contribution, flexible working options, employee counseling and a Benefits Portal with various deals and discounts. Invest and Plan Your Future. We help you plan and invest for the future with competitive pay and programs: your base salary, bonus programs, opportunities to own company shares, discounts on company products, referral bonus, pension plans and a digital pension advisory tool. Grow Your Skills and Career. We commit to helping you grow with ongoing performance and development conversations, global career opportunities, access to our Schneider Career Hub for new positions
AI/ML Engineer
What will you do? As a AI/ML Engineer at Rebtel you will define how AI is done at Rebtel. What tooling we standardise on, how we evaluate models we put in front of real users, what "good" looks like for our prompts and our pipelines. AI is going from a side project to the core of how Rebtel operates and what we ship to our users. We're hiring the second engineer on our ML/AI subteam to help build it classical ML for the business, LLM-powered systems for the product, and a clear production mindset on both. You'll sit inside the Data team, report to our Head of Data, and partner with one other ML/AI engineer to shape this capability from the ground up. Areas of ownership: You'll own work across two complementary tracks, and you'll ship in both. Classical ML, in production, for operational leverage Risk and fraud models across payments, top-ups, and account behaviour Churn prediction and retention modelling on a user base of a million-plus Forecasting, pricing, segmentation, and the next batch of operational problems we haven't tackled yet Owning models end-to-end scoping with stakeholders, building, deploying, monitoring, retraining LLMs and AI agents, from internal automation to in-product features Start with our customer support agents and automations: RAG pipelines, prompt orchestration, tool-use, evaluation harnesses Move LLM capability into the product as user-facing features Help guide the company on where AI actually creates leverage, what to build, what to buy, what to ignore and turn the good ideas into shipped systems Requirements: You are an excellent communicator and collaborator. We work in English, but you will hear many languages in our Stockholm office 4+ years of hands-on ML engineering in Python, with real production ownership not just notebooks Strong fundamentals in classical ML: feature engineering, model selection, validation, and the unglamorous parts of keeping a model healthy in prod A genuine production mindset: monitoring, retraining, eval harnesses, CI/CD for models, and the instinct to debug when something drifts at 2am Comfort working the whole loop: stakeholder scoping → data → model → deployment → measurement → iteration Strong written and spoken English, and the ability to translate between business problems and ML ones Hands-on experience with LLM frameworks — LangChain, LangGraph, LlamaIndex, or equivalents Built RAG systems, agentic workflows, or LLM-backed products that real users (or real internal teams) actually used Comfortable with vector databases, embeddings, prompt evaluation, and measuring LLM systems with something more rigorous than vibes Obsession with staying up-to-date on developments in the AI space Experience with a major cloud (AWS / GCP / Azure), containers, and a modern data stack Experience in MLOps tooling: MLflow, Airflow, Kubernetes and feature stores is a plus Background in fintech, payments, telecom, or other regulated / operational domains is a plus Why Rebtel? Rebtel has been connecting people across borders for nearly 20 years. Today, we’re profitable, growing, and at a pivotal moment in our journey. As we enter our next phase, we’re building an organisation designed for speed, ownership, and real impact, where every role contributes directly to shaping what comes next. This is a place with global ambition and a strong foundation, where ideas move quickly and decisions matter. You won’t get lost in layers of process or slow-moving structures. Instead, you’ll find the space to take ownership, collaborate across teams, and make meaningful contributions from day one. Based in Stockholm, we bring together a diverse, international team united by a shared purpose: to simplify the way people connect worldwide. At Rebtel, you are the most important asset and we strive to provide a comprehensive package of benefits and perks that enhance your well-being and work experience. Here are some of the things you can expect from us: Pension Plan Health Checkups, Influenza shots and Private Medical Insurance Dental Insurance Occupational insurance Wellness allowance (5,000 SEK) Discount on gym memberships Bonus program Extra parental pay 30 days annual vacation Monday breakfasts Relocation Support, if you're joining us from afar, we'll assist you in making a smooth transition. We are Rebtel. We come from all around the world to create products for anyone who has crossed a border. We believe in equal opportunity and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
Data Scientist inom paketlogistik till PostNord
Vill du använda Data Science för att utveckla ett av Sveriges största paketnätverk? På PostNord får du göra data till beslut. PostNord befinner sig i en förändringsresa med stora investeringar i framtidens paketverksamhet. Nu söker de en Data Scientist som vill använda stora mängder data för att skapa konkreta förbättringar i paketverksamheten. Här får du kombinera Data Science, prognostisering och optimering med ett verksamhetsnära och strategiskt perspektiv.PostNord hanterar dagligen mycket stora volymer paket och samlar in stora mängder data genom hela paketflödet. Potentialen är stor – och mycket av informationen kan användas mer för att förstå, förutse och optimera verksamheten. I den här rollen får du vara med och identifiera möjligheterna, utveckla modeller och omsätta analyser till beslutsunderlag som kan påverka allt från bemanning och kapacitet till terminaler, transporter och framtida nätverksdesign. Vi erbjuder dig PostNord erbjuder en roll där din specialistkompetens får stor möjlighet att påverka verksamheten. Du kommer in i ett spännande skede där organisationen utvecklar hur data används för att fatta bättre beslut inom paketaffären. Möjlighet att arbeta med stora datamängder från en omfattande och komplex paketverksamhet. En verksamhetsnära Data Science-roll där dina analyser omsätts till konkreta beslut och förbättringar. Möjlighet att påverka hur PostNord framåt arbetar med analys, prognostisering och optimering inom paketverksamheten. Kombinera strategiskt arbete och hands-on Data Science, där du både utvecklar modeller och omsätter resultaten till verksamhetsnytta. Vara med när PostNord utvecklar paketverksamheten och investerar i hur framtidens paketnätverk ska fungera. Det här gör du hos oss Här arbetar du med frågor där data kan ge bättre förståelse för både dagens paketflöden och framtidens pakethantering. Tillsammans med verksamheten identifierar du vad som behöver lösas och hur data kan bidra. Analyserar stora datamängder och omsätter dem till konkreta beslutsunderlag och strategiska beslut inom paketverksamheten. Utvecklar och implementerar tidsserie- och prognosmodeller för paketflöden och paketvolymer. Använder maskininlärning för att utveckla prognosernas noggrannhet och tillförlitlighet. Arbetar med optimering av exempelvis kapacitet, resursallokering, ruttplanering och bemanning. Identifierar tillsammans med verksamheten vilken data som kan användas för att lösa problem och skapa affärsvärde. Använder geodata för analyser kopplade till exempelvis leveransrutter, terminalverksamhet och nätverksdesign. Samarbetar med bland annat Data Engineers och andra specialistfunktioner kring data, AI och Machine Learning. Ditt team och arbetsplats Du tillhör PostNords affärsområde Paket och arbetar i en central funktion med uppdrag mot hela paketorganisationen för Sverige. Rollen är placerad i Stockholm och PostNord tillämpar ett upplägg med tre dagar i veckan på arbetsplatsen. I rollen kan du även stötta olika delar av paketverksamheten utifrån deras behov och utmaningar. Mer om dig För att lyckas i rollen har du minst fem års erfarenhet inom Data Science och är van att arbeta med stora datamängder. Du har erfarenhet av tidsserieanalys, prognostisering och optimering samt mycket goda kunskaper i programmering, exempelvis Python. Du har arbetat med relevanta Data Science-bibliotek och verktyg såsom NumPy, Pandas, Scikit-learn eller TensorFlow och har erfarenhet av matematiska optimeringstekniker. Erfarenhet av geospatial analys och GIS-verktyg är meriterande. Du har en kandidat- eller masterexamen inom datavetenskap, statistik, operationsanalys eller motsvarande område och behärskar svenska och engelska mycket väl. Det viktiga är samtidigt att du inte enbart vill arbeta med modeller och data isolerat. Du är nyfiken på verksamheten och vill förstå vilka problem som behöver lösas och hur dina analyser kan bidra till resultat. Du kan hantera komplex information, se helheten och omsätta analys till tydliga rekommendationer. Rollen innebär många samarbeten, vilket gör att du behöver kunna kommunicera dina slutsatser på ett begripligt sätt och trivas med att arbeta tillsammans med olika delar av organisationen. Så här får vi kontakt I den här rekryteringen har vi valt att samarbeta med Ada Digital som strävar efter en transparent, inkluderande och snabbrörlig rekryteringsupplevelse. Vi vill veta mer om dig och din potential! Du söker tjänsten enkelt och behöver inte bifoga några dokument. Det räcker med en motivering till varför du söker tjänsten och om du saknar CV kan du bifoga din LinkedIn-profil. Följ sedan din ansökan live via vår hemsida. Urvalet sker löpande och tjänsten kan bli tillsatt före sista ansökningsdatum. Är du nyfiken och vill veta mer innan du söker? Hör av dig till ansvarig rekryterare. Vi ser fram emot att få kontakt med dig!
Data-science roll
Vi söker en Data Scientist / Machine Learning Engineer som får en central roll i att utveckla och förbättra våra maskininlärningsmodeller och datapipelines. Du kommer att arbeta nära grundarteamet och bidra till forskning och produktutveckling inom AI.
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