Data Scientist

Data Scientist

Location: São Paulo, Brazil | Type: Contract (3 months) | Setup: Hybrid | Experience: 5+ years | Pay: Up to $35/hr

About the Role

We're hiring a Data Scientist for a three-month engagement where you'll take a workstream from business question to deployed model, not just to a notebook. That means framing the problem with the client, building the model, and getting it running with real MLOps around it.

The client is a crafts-based digital product studio backed by a global strategy consulting parent, delivering data and software work to large enterprises. The work is case-shaped: short cycles, senior stakeholders in the room, and analysis that has to hold up when a partner or a client executive pushes on it. You'll be in São Paulo on a hybrid schedule with the local team.

Three months is a real constraint, so this suits someone who moves without waiting for the problem to be pre-defined.

What You'll Do

• Translate a business problem into an analytical workplan, then drive your portion of the case end to end with minimal supervision
• Build models across supervised, unsupervised, and deep learning approaches, choosing the method that fits the data and the deadline
• Deploy and operationalize what you build using Docker, Terraform, MLflow, and GitHub Actions rather than handing off a notebook
• Stand up and manage the data pipelines your modeling depends on in Airflow, Beam, Spark, or NiFi
• Write Python that another engineer can pick up: tested, structured, and built for a real ML workflow
• Coordinate across teammates and cross-functional collaborators so the analysis lands in the product, not beside it
• Synthesize findings into client-ready recommendations and materials, and present them yourself

Qualifications

Core Data Science

• 5+ years in data science, machine learning, or advanced analytics
• Deep Python proficiency: data structures, algorithms, object-oriented design, testing, and scalable code for ML workflows
• Strong foundation in machine learning and deep learning, spanning supervised and unsupervised learning, reinforcement learning, NLP, and modern architectures
• Working knowledge of SQL or NoSQL databases
• Bachelor's degree in Computer Science, Engineering, Statistics, Econometrics, Information Sciences, or a related quantitative field

Deployment and Pipelines

• Experience deploying and operationalizing models with containerization (Docker, Terraform) and MLOps tooling (MLflow, GitHub Actions)
• Proficiency building and managing data workflows and pipelines for modeling (Airflow, Beam, Spark, NiFi, or similar)
• Hands-on experience on at least one major cloud platform (AWS, Azure, or GCP)

Client-Facing

• Ability to turn ambiguous business problems into an actionable workplan and own a slice of it without hand-holding
• Experience coordinating work across teammates and cross-functional collaborators
• Strong client communication and presentation skills, with the judgment to know what a client executive actually needs to see

Why Join Us

You'll work with a team that treats analysis like a deliverable someone will act on, not a report that gets filed. Engineers, designers, and data people sit close together, cycles are short, and the bar for what gets shown to a client is high.

If you like the pace of case work but want your models to actually ship, this is a good three months.