Product Manager, Data Insights
- Compensation
- Not disclosed
- Location
- Stockholm, SE
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 3+ years
- Category
- Product
- Posted
Skills
Must have
- Hands-on data proficiency across both paradigms: you can build and validate ML proof-of-concepts (data exploration, feature engineering, model training, evaluation) using Python and standard ML toolin
Nice to have
- Experience with time-series or logistics domain data: carrier performance modelling, routing optimization, ETA prediction, or related domains.
Full description
About UsnShift is the leading global provider of cloud delivery management solutions (SaaS), we enable the frictionless shipment and return of almost one billion shipments across 190 countries each year. We are headquartered in London and Oslo and have over 500 employees across offices in Sweden, Finland, Norway, Denmark, the United Kingdom, Poland, the Netherlands, Belgium, and Romania.
Our software is used by many of the world leading e-commerce, retail, manufacturing, and 3PL shippers due to us having over 1000 carriers integrated into our platform, nearly 3 times more than our competitors!
If you buy goods online, there is a strong chance that nShift has powered that delivery, so come and join us as we shape the future of shipping, one frictionless journey at a time.
About you
You think like a product manager and work like a data scientist. You have shipped ML-powered products to real customers and can point to the decisions you made, not just the ones made around you. Messy data, ambiguous model outputs, and stakeholders who don't yet see why the data matters are familiar territory.
You think in terms of compounding: how every data point collected today improves predictions tomorrow, and how that improvement builds a position competitors cannot close. Data insights is nShift's path from a tool company to an intelligence platform, and that scope motivates you rather than overwhelming you.
You are as comfortable in a Jupyter notebook as in a leadership meeting, and you know when each is needed.
Purpose of role
The mission is to define what nShift builds with that data, validate it before engineering commits, and ship intelligence products that help shippers make better decisions. A shipper asking "how can I improve my delivery experience" should get an answer powered by the full network, not just their own history. Done well, that becomes a compounding intelligence layer: every data point collected today improves suggestions tomorrow, and the improvement creates a position no competitor can close.
The intelligence layer draws from two sources. Structured operational data, such as shipment telemetry and carrier performance, feeds statistical models and predictions. Qualitative data, such as customer support interactions, delivery exception messages, and community feedback, carries signal that numbers alone cannot surface. LLMs make that signal extractable and usable at scale. This role owns both.
The role sits at the intersection of product management and data science. You have the technical depth to build ML proof-of-concepts independently and the commercial judgment to translate those capabilities into products customers pay for. You write the strategy and the first notebook.