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Network Analyst (Data Analyst)

Remote role Full-time Open position

We’re not here to waste your time. Read this carefully and only apply if you’re ready to do real work that matters.

What the job entails

  • You’ll be part of a small, sharp team applying Network Science to real-world business problems inside a high-impact AI exploration unit. We’re turning raw data into meaningful graphs, analyzing connections, detecting hidden patterns, and building tools to help autonomous agents make better decisions.
  • You won’t be optimizing dashboards or stuck tweaking marketing reports. You’ll be building intelligence infrastructure.

    • Your main tasks

  • Transform tabular data into graphs that expose structure and behavior.
  • Research, prototype, and deploy graph algorithms to detect communities, centrality, anomalies, and more.
  • Build and maintain ETL pipelines for graph data extraction and enrichment.
  • Design graph visualizations to support human and machine understanding.
  • Collaborate with Data Scientists and LLM Engineers to integrate network-based reasoning into our autonomous systems.
  • Experiment often, document clearly, and ship code that matters.

    • Technologies / techniques used

  • Python (heavy use)
  • SQL (PostgreSQL, BigQuery)
  • Graph libraries (e.g. NetworkX, cuGraph, Graphistry)
  • Visualization tools (Plotly, Dash, D3, etc.)
  • Neo4j or other graph databases
  • GCP (preferred) or any major cloud provider
  • GitHub + CI/CD pipelines

    • What you'll need

  • Strong Python and SQL skills.
  • Ability to break down abstract problems into experimental pipelines.
  • Clear communication skills in Portuguese and English.
  • Curiosity and initiative. You find answers, you don’t wait for them.
  • Solid data wrangling and visualization abilities.
  • Willingness to go deep into Network Science, even if you’re not an expert (yet).

    • Nice to have

  • Experience with NetworkX, Neo4j, or any graph database.
  • Previous Experience or openness to learn and work with Elixir codebases
  • Background in graph theory, link prediction, community detection.
  • Knowledge of probabilistic modeling or LLM integration with graph-based systems.
  • Familiarity with GCP and large-scale data pipelines.

    • Recruiting process outline

  • Open-ended technical case – you’ll analyze a small graph dataset and extract insights.
  • Technical interview – discuss your solution and background.
  • Cultural interview – aligned expectations, mutual fit.
  • If you’re not interested in doing a real technical assessment or engaging in an honest conversation, don’t apply.

    • Additional Information

    Diversity and inclusion:

    We believe in social inclusion, respect, and appreciation of all people. We promote a welcoming work environment, where each CloudWalker can be authentic, regardless of gender, ethnicity, race, religion, sexuality, mobility, disability, or education.

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