Senior Technical Product Owner (ML Engineering)

sennder is Europe’s leading digital freight forwarder at the intersection of where technology meets logistics. Through our proprietary transportation operating system, built by our in-house tech teams, we not only connect shippers to our fleet of thousands of trucks, but also improve how they move products in sustainable, cost-efficient, and transparent ways - making the logistics industry fit for the future. In a traditional industry, we’re growing and moving fast to digitally automate all road logistics processes. You can be part of one of Europe’s latest growth stories as we fast-forward road logistics into digitalization. Get to know us, our culture, green business, funding history, and more on our blog here.

• Own product delivery with a top-notch highly specialized team to provide product functionality while meeting and/or exceeding our operational KPI targets;
• Drive the technical backlog of our automated ML-based shipper-to-carrier assignment experience and its underlying technology, including external data services, feature construction pipelines, embedded heuristics, machine learning services and proprietary technology;
• Champion data governance practices across the organization, contributing to pushing data quality to the next level while aligning stakeholders to take business decisions in a data driven fashion;
• Promote teamwork and Agility as the easiest path for team success;
• Manage external data providers and define a roadmap for their testing/onboarding/offboarding and related impact on the performance on our ML technology and consequent business impact;
• Be customer-centered by driving Product discovery on the ML System Design space to build the right stuff;
• Define success criteria, goals, and metrics for your initiatives together with the technical and operations teams;
• Set up the right bridges and ways of working towards working truly cross-functionally with Operations teams on designing ML products;
• Prioritize ruthlessly based in your teams’ focus metrics with top-notch communication from/to/with stakeholders, guaranteeing the team’s focus and scalable value delivery;

• Highly Technical Product Experience: 2+ years of experience leading highly technical product development (machine learning, computer vision or NLP);
• Experience having worked with end to end Machine Learning product delivery, lifecycle management and the related product tradeoffs;
• Strong background on leading problem solving on cross-functional teams using Agile processes (e.g.: Scrum, Kanban, Scrumban, XP);
• Excellent verbal and written communication skills, with the ability to inspire and influence team members with the vision;
• An empathetic person with a bridge-building mindset;
• Able to make informed decisions based on qualitative user insights and quantitative user data by conducting research, A/B tests, and analyzing operations data;
• Fluent in English;

• Background as individual contributor on Data Science and Machine Learning space;
• Proven track record of delivering results in a fast-paced, dynamic, tech-first environment and driving innovation on behalf of internal/external stakeholders;
• Experience on driving data products within AWS cloud platform;
• In-depth knowledge of modern software development and machine learning engineering practices;
• Exposure to OKR-based strategy canvas;
• Ms.c. (or higher degree) on Computer Science;

• A fast-growing scale-up, where your work will make an impact on our growth and lead to several careeropportunities;
• An international team of 900+ people with 65+ nationalities spread across 11 offices in 7 countries with English as our company language;
• Culture of trust, constructive feedback and self-organization with a forever-agile mindset;
• A quarterly feedback and review process for personal development;
• A structured promotion process, providing everyone with fair and transparent career growth;
• Learning and development opportunities on the job and through conversations with your manager;
• Various opportunities to connect with colleagues, formally and informally, digitally or in person (whenallowed), through regular team events, company get-togethers, and partnership events with other companiesand local organizers.;
• When in office: unlimited snacks, drinks, and fruits;
• Compliance with COVID-19 restrictions when required with remote interviews, onboarding, and working;