About this role
Professionals who enjoy untangling messy high-volume telemetry and network traffic data will thrive in this environment. Plume operates a cloud-controlled experience platform for smart spaces, utilizing AI and machine learning to serve over 60 million locations globally through partnerships with major internet service providers.
In this capacity, the incoming practitioner designs, builds, and deploys data-driven models while shaping the underlying datasets, features, and analytical pipelines. The group tackles complex forecasting, anomaly detection, and optimization problems, requiring team members to translate business and product needs into production-ready solutions under tight schedules.
What you will do
- Manipulate, clean, and transform large-scale datasets consisting of network and device telemetry for modeling and analysis.
- Design and implement feature engineering strategies that enhance model accuracy, interpretability, and robustness.
- Use SQL and Python libraries such as Pandas, NumPy, and Scikit-learn to explore data and build analytical pipelines.
- Translate product or business needs into well-scoped analytical tasks and model development plans.
- Build and evaluate machine learning models for anomaly detection, forecasting, and optimization.
- Collaborate closely with engineering and product teams to integrate models into production systems and monitor performance.
- Contribute to MLOps workflows for model deployment, validation, and monitoring.
What you need
- Demonstrate strong programming skills in Python alongside experience with core data science libraries.
- Maintain solid SQL skills for querying, aggregating, and joining complex datasets.
- Bring proven experience in transforming messy, high-volume data into structured, high-quality inputs for modeling.
- Possess a deep understanding of feature extraction, selection, and transformation for predictive modeling.
- Show a strong grasp of statistics, probability, and applied machine learning.
- Exhibit the ability to understand requirements, scope solutions, and deliver high-quality results on tight timelines.
- Communicate and collaborate effectively across engineering, product, and data functions.
Skills and tech stack
Questions candidates ask
Where is this job located?
The role is based in Ljubljana, Slovenia, or Wroclaw, Poland. Plume delivers services to over 60 million locations globally through these and other operations.
What tools and technologies will I use?
The tech stack centers on Python, SQL, and associated data science libraries such as Pandas, NumPy, and Scikit-learn. Practitioners also contribute to MLOps workflows for model deployment, validation, and monitoring.
What will I work on day-to-day?
Day-to-day work involves designing, building, and deploying data-driven models that extract insight from network traffic and telemetry data. Responsibilities also include shaping features, building machine learning models for forecasting and anomaly detection, and collaborating with engineering teams.