Top Tech Jobs & Startup Jobs

Lead the Data Discovery & Experience chapter by coaching professionals, developing capabilities, establishing technical standards, and guiding API, Data Product, and Data Discovery initiatives. Partner with product, architecture, and engineering teams to improve user value and adoption. Promote AI literacy, experimentation, responsible technology use, continuous improvement, and professional growth while supporting recruitment, onboarding, knowledge sharing, and technical strategy.

Develop and productionize machine learning and advanced analytics solutions across customer acquisition, sales, customer service, and claims. Responsibilities include data preparation, model and pipeline development, deployment, monitoring, stakeholder engagement, technical guidance, opportunity identification, and coaching junior data scientists. The role requires Python and SQL proficiency, software development practices, and collaboration across Nordic agile teams. Azure and Databricks experience is beneficial.

Develop and maintain C#/.NET APIs, microservices, and Azure integration solutions for an insurance transformation program. Improve DevOps maturity, test automation, CI/CD pipelines, feature toggling, security, monitoring, and quality standards. Collaborate with architects, DevOps engineers, and product teams while mentoring developers and enabling other squads to adopt modern engineering practices.

Develop and improve risk and pricing models for Swedish personal insurance customers using statistical modeling, machine learning, and large-scale data analysis. Own the end-to-end data science process, including implementation, monitoring, and iterative improvement in a modern analytics platform. Collaborate across Nordic analytics teams and communicate complex insights effectively. The role requires SQL and Python programming, STEM education, and fluency in Swedish and English.

Lead QA practices for Motor Claims software, combining manual and automated testing across API, UI, integration, and end-to-end workflows. Create test plans, define coverage using risk-based approaches, analyze automation scope and results, manage defects, and support Agile releases. Collaborate with developers, product owners, analysts, UX, and business users while advancing shift-left testing and AI-assisted test design, analysis, documentation, and optimization.

Develop APIs, integrations, and applications powering personalized customer journeys through Bloomreach Engagement and CRM channels. Build B2C and B2B solutions using .NET, C#, Azure, REST APIs, microservices, asynchronous messaging, and Azure data services. Integrate cloud, on-premise, partner, and first-party data sources while applying Agile, DevOps, CI/CD, information security, and GDPR principles. Collaborate with Nordic developers and business stakeholders to deliver secure, event-driven customer communications.

Advise teams on security architecture and secure solution design, with a strong focus on AI security and emerging technologies. Conduct risk assessments, develop security principles and frameworks, support Security by Design, and guide cloud, application, DevSecOps, software development, and supply chain security decisions. Collaborate with architects, developers, platform teams, risk specialists, privacy experts, and business stakeholders to translate complex security requirements into practical recommendations.

Build AI-powered experiences, scalable platform capabilities, APIs, MCPs, and Data Products. Improve data and API discovery, access, and usage while collaborating with product, architecture, engineering, and business teams. Apply platform engineering and product thinking to deliver secure, practical AI solutions, contribute to AI literacy, and support agile ways of working. The role requires software engineering experience, hands-on production AI engineering, and familiarity with modern AI, cloud, API, and data technologies.

Build AI-powered platform capabilities for API, MCP, and Data Product discovery and consumption. Develop AI agents, integrations, and scalable cloud-native solutions while improving secure access, developer experience, and enterprise data usage. Collaborate with product managers, architects, engineers, and business stakeholders to turn AI opportunities into practical solutions. Contribute to AI literacy, agile delivery, and platform engineering across insurance technology teams.

Leads and develops a distributed MarTech data engineering team while contributing technically to Azure Databricks solutions. Responsibilities include mentoring engineers, establishing engineering standards, and delivering reliable, scalable, cost-efficient data products, pipelines, and lakehouse services. The role drives data quality, governance, CI/CD, Infrastructure as Code, testing, security, automation, and operational excellence across Agile and DevOps teams.