Data Science Specialist – Machine Learning

📋 Description

• Serve as the technical authority for ML/AI and data within the Investment Products Community, shaping architectural standards and product choices throughout the organization.

• Establish the technical vision and strategic roadmap for AI/ML products and solutions, prioritizing based on impact, risk, and feasibility in collaboration with key stakeholders.

• Design and develop data and ML pipelines (training, evaluation, inference) with an emphasis on reliability, performance, and observability.

• Advance agent/multi-agent architectures (orchestration, memory, tools, guardrails, and security), balancing cost, latency, and quality.

• Enforce guardrails and implement security and privacy practices (LGPD, DLP, access control, prompt injection mitigation).

• Perform trade-off analyses and make architectural decisions (build vs. buy, platform vs. service) considering FinOps and scalability factors.

⛳️ Requirements

• Demonstrated applied Data Science experience with ML/AI implemented in production and resulting in measurable impact.

• Expertise in Python and data/ML libraries (Pandas, NumPy, scikit-learn; familiarity with PyTorch/TensorFlow is a plus).

• Proficient in code versioning (Git/GitHub) and possess strong engineering practices (code review, CI/CD).

• Skilled in data modeling and data architecture; advanced SQL; experience with both relational and non-relational databases.

• Familiarity with Big Data and distributed processing (Spark) and experience with batch/streaming pipelines.

• Knowledge of MLOps/LLMOps, including experiment tracking, model registry, observability, monitoring, and drift detection.

• Advanced knowledge of cloud platforms (AWS preferred: S3, Lambda, Glue; additional knowledge of Step Functions, ECS/EKS, SageMaker is beneficial).

• Experience with RAG and vector databases (pgvector, OpenSearch, Pinecone, FAISS), LLM/agent evaluation, prompting techniques, caching, and optimization.

• Familiarity with Big Data/Analytics ecosystems (Databricks/EMR, Kafka/Kinesis) and FinOps for AI workloads.

• Proven experience in developing agentic solutions for processing substantial volumes of data.

• Experience with .NET Core.

🏝️ Benefits

• Freedom to work from any location.

• Flexible working hours.

• Education allowance.

• Access to an in-house career development tool.

• Participation in internal guilds and study/interest groups.

• Health insurance coverage.

• Dental plan.

• Partnership for medication purchases.

• 24/7 telemedicine services.

• Free online therapy options.

• Access to Wellhub.

• Extended maternity leave.

• Extended paternity leave.

• CAZ – Zuppers Support Center.

• Meal and food vouchers.

• Life insurance coverage.

• Transportation allowance.

• Home office allowance.

• Childcare allowance.

• Phone plan allowance.

• Profit Sharing (PLR).