Position Title:  Senior Enterprise Data Scientist

At PMI, we’ve chosen to do something incredible.

We’re totally transforming our business and building our future on smoke-free products with the power to deliver a smoke-free future.

With huge change, comes huge opportunity. So, wherever you join us, you’ll enjoy the freedom to dream up and deliver better, brighter solutions and you will have the space to move your career forward in many different areas/directions.

PMI’s journey to a smoke-free future implies a shift from a tobacco manufacturer to a science and technology-based consumer facing organization.

Such a shift creates an abundance of unique and transformative IT projects to match all levels of skills and ambitions. You’ll feel like you’re working in a start-up – with the freedom to shape and define the future of digital, but with the support and scope of a vast global business. You’ll get a chance to work with cutting-edge technologies (e.g., Cloud, APIs, AI) as well as management practices (e.g., Agile, Design Thinking, Product Management). Our environment is fast-paced and highly collaborative. If you want the freedom to find new ways to connect with consumers, there’s no better place to progress your career.

At our Global Data & Analytics Hub we work in a product-based framework, turning business problems into mathematical/statistical solutions and shipping them as production-grade pipelines that support real business processes. As a Senior Data Scientist, you will operate in one of two complementary specializations — and you're expected to be strong in the shared core regardless of track:

• Track A — Classical / Applied Machine Learning: designing, training, evaluating and deploying predictive models (classification, clustering, regression, forecasting, recommendation, computer vision) and the pipelines that keep them reliable in production.
• Track B — AI / GenAI Engineering: building LLM-powered applications, RAG systems and multi-agent workflows (prompt engineering, tool/function calling, evaluation and guardrails) on top of foundation models.

Either specialization is acceptable — we are supporting solutions that require both tracks.

Principal Accountabilities (shared core):

• Convert business problems into well-framed mathematical/statistical or AI problems and deliver them as production-ready code through CI/CD, code review and collaboration tools.
• Interact directly with business stakeholders to shape viable data/AI products, managing expectations on scope, timeline and quality across PoCs and delivery.
• Act as a Data Science lead within projects — owning technical decisions end-to-end, driving architecture discussions, and being accountable for delivery quality.
• Coach and uplift more junior colleagues through pair-programming, code review, and knowledge sharing in the Advanced Analytics Community of Practice.
• Work independently and autonomously — conceptualizing, prototyping and implementing solutions with minimal supervision in a fast-paced, ambiguous environment.
• Work efficiently in Scrum teams and contribute to reproducibility, test coverage and engineering standards.

Skills & Competences (shared core):

• Bachelor's (or higher) in a technical/quantitative field — Mathematics, Computer Science, Statistics, or Engineering.
• 3+ years of hands-on Data Science / ML experience.
• Programming: Python (mandatory), SQL is a plus.
• Production-grade coding: clean, modular, testable code (SRP, dependency inversion), unit/integration testing, packaging, logging, traceability and code review discipline.
• CI/CD & SDLC: Git/Bitbucket, automated testing, versioning, CD/CI pipelines.
• Cloud — AWS: proficiency across the AWS stack including Amazon SageMaker (training/hosting/inference), Bedrock, S3, Lambda, ECS, API Gateway.
• MLOps: deploying, monitoring and maintaining models/agents in production (versioning, observability, drift/performance tracking).
• Data Governance: data privacy, security and compliance awareness.
• Agile methodologies and a hypothesis-driven approach.
• Leadership & soft skills: ability to lead as a DS within a project, mentor junior colleagues, communicate with stakeholders, and work independently.

Track-Specific Skills:

Track A — Classical / Applied ML

• ML fundamentals: statistics, scikit-learn / XGBoost / PyTorch, feature engineering, experiment design & A/B testing.
• SageMaker Training Jobs & Pipelines: training/hyperparameter tuning; end-to-end orchestration (prep → train → evaluate → register → deploy).
• Airflow orchestration: DAG-based scheduling of data/ML pipelines with dependencies and backfills.
• Automated retraining & MLOps: drift/performance-triggered retraining, Model Registry versioning, champion/challenger evaluation.

Track B — AI / GenAI Engineering

• LLMs & frameworks: LangChain/LangGraph, RAG and vector stores, prompt engineering, guardrails, context/token management.
• Agent evaluation: eval frameworks, offline eval sets, groundedness/quality scoring, human-feedback loops, regression suites.
• LangSmith deployments & observability: tracing, monitoring and debugging agents in production (latency, cost, tokens, hallucination tracking), integrated into CI/CD.

WHAT WE OFFER YOU?

Permanent local contract with a competitive salary plus Tabaqueira’s employee benefit including:

• Life and Health insurance

• Employee Pension Plan

• Hybrid working model

• Growing opportunities within the Company, both at national and international level

• Possibility of development in both Controlling and Business Partnering areas

• Very diverse and international work environment

Please note that only on-line applications will be taken into consideration.

No relocation package available.