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Senior Data Scientist (Find My)

Apple· Machine Learning and AI
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Malmö, SwedenFull-timePosted 2w ago

About the role

Senior Data Scientist focused on navigating large-scale spatiotemporal datasets for Apple’s Find My crowd-sourced network. Owns analyses and models end-to-end from exploration to production handoff, works closely with engineering, and communicates findings to non-technical stakeholders. Role requires on-site work in Malmö, Sweden, with English as the working language.

Responsibilities

  • Hands-on data science experience where your work reached production and was used. You’ve owned it from the first question through handoff, and you’ve seen a model that looked right offline behave differently on real data and worked out why.
  • Strong geospatial fundamentals: geometry operations, spatial joins, spatial statistics, and coordinate reference systems. You know why computing area in EPSG:4326 gives the wrong answer. Tools such as GeoPandas, Shapely, or PySAL.
  • Experience with raw sensor data: cleaning noisy, irregular observations, combining sources, and deriving new signals that hold up on real data.
  • Proven modeling range, with tools such as scikit-learn or XGBoost for classical predictive work and Prophet or ARIMA for time-series forecasting, with deep learning, such as PyTorch, when the problem calls for it. You also know when the simpler model is the right one.
  • Experience with spatial databases and distributed spatial processing, such as PostGIS or Apache Sedona, and with discrete global grid systems for hierarchical spatial indexing.
  • Experience from location-heavy domains such as mobility, delivery, logistics, or mapping.
  • Experience analyzing data too large for one machine. You care about query and algorithm cost, and when a spatial join across billions of observations takes hours, you find out why before asking for a bigger cluster.
  • Deep Python, used to get real answers. You know when a quick script settles the question and when it needs to become something that lasts, and you move fast in both modes.
  • Experience working under privacy constraints, such as aggregation thresholds or differential privacy.
  • Your work hands off cleanly to engineering: reproducible, tested, and documented

Qualifications

  • Hands-on data science experience where your work reached production and was used.
  • Strong geospatial fundamentals: geometry operations, spatial joins, spatial statistics, and coordinate reference systems. You know why computing area in EPSG:4326 gives the wrong answer. Tools such as GeoPandas, Shapely, or PySAL.
  • Experience with raw sensor data: cleaning noisy, irregular observations, combining sources, and deriving new signals that hold up on real data.
  • Proven modeling range, with tools such as scikit-learn or XGBoost for classical predictive work and Prophet or ARIMA for time-series forecasting, with deep learning, such as PyTorch, when the problem calls for it. You also know when the simpler model is the right one.
  • Experience with spatial databases and distributed spatial processing, such as PostGIS or Apache Sedona, and with discrete global grid systems for hierarchical spatial indexing.
  • Experience from location-heavy domains such as mobility, delivery, logistics, or mapping.
  • Experience analyzing data too large for one machine. You care about query and algorithm cost, and when a spatial join across billions of observations takes hours, you find out why before asking for a bigger cluster.
  • Deep Python, used to get real answers. You know when a quick script settles the question and when it needs to become something that lasts, and you move fast in both modes.
  • Experience working under privacy constraints, such as aggregation thresholds or differential privacy.
  • Your work hands off cleanly to engineering: reproducible, tested, and documented

Skills

Required:Hands-on production data scienceGeospatial fundamentalsSensor data handlingModeling toolsSpatial databases/distributed processingDomain experienceHandling large-scale dataPythonPrivacy & data protectionEngineering handoff
Last updated Oct 23, 2026. Interested? Apply on the company site.

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