Data Scientist

IT People Innovation; Portugal; Híbrido; EUR 55 000 - 75 000; Tempo integral

Resumo da oferta

IT People Innovation in Lisbon is seeking a Data Scientist to join a team building predictive models for a major utilities company, blending time-series forecasting with generative AI. You will design and validate models for price forecasting and market signals, use LangChain/LlamaIndex and other AI tooling, and work with traders and engineers to productionize solutions.

A autonomous, curious coder comfortable in a hybrid, fast-moving setting, with 3–5 years in data science and strong Python

Qualificações

• 3–5 years of experience as a Data Scientist or ML Engineer.
• Hands-on Python and ML stack experience.
• Practical use of generative AI tools in workflows.
• Strong predictive modeling and time-series skills.
• SQL proficiency with real-world datasets.
• Experience deploying or maintaining models is a plus.

Responsabilidades

• Design, build, and validate predictive models for price forecasting and market signals.
• Leverage generative AI tools to speed up research and feature engineering.
• Work with time-series-heavy datasets from client markets.
• Translate needs into modeling problems and present outputs clearly.
• Test, monitor, and refine models in live market conditions.
• Collaborate with client engineers to productionize models.
• Document methodology and findings for technical and non-technical stakeholders.

Conhecimentos

Python

Pandas

Scikit-learn

XGBoost/LightGBM

PyTorch/TensorFlow

Generative AI / LLM tools

Time-series forecasting

SQL

Model deployment

Ferramentas

LangChain

LlamaIndex

RAG pipelines

Copilot-style coding

Descrição da oferta de emprego

Data Scientist – Predictive Modeling & Generative AI

Location

Lisbon

About the Role

We are building a team to develop predictive algorithmic models for a major utilities company. This is a high-impact, applied data science role where you'll work at the intersection of machine learning, generative AI, and quantitative modeling to help anticipate market movements and price dynamics.

What You'll Do

• Design, build, and validate predictive models for price forecasting, demand/supply dynamics, and market signal generation
• Use generative AI tools (LLM-assisted coding, RAG pipelines, prompt engineering, agentic workflows) to speed up research, feature engineering, and model iteration
• Work with large, messy, time-series-heavy datasets specific to our client's market
• Translate trading team needs into modeling problems, and translate model outputs back into insights that can be acted on
• Continuously test, monitor, and refine models in a live, fast-moving market environment
• Collaborate with client engineers to embed models into production workflows
• Document methodology and findings clearly for both technical and non-technical stakeholders

What We're Looking For

Experience & Technical Skills

• 3–5 years of experience as a Data Scientist, ML Engineer, or similar applied role
• Strong hands-on experience with Python and standard ML/data stacks (pandas, scikit-learn, XGBoost/LightGBM, PyTorch or TensorFlow)
• Practical experience using generative AI / LLM tools in a real workflow (e.g., Copilot-style coding assistants, LangChain/LlamaIndex, RAG, prompt engineering, agentic pipelines) — this is a hands-on requirement, not just familiarity
• Solid grounding in predictive modeling and time-series forecasting techniques
• Comfortable working with SQL and large, real-world (i.e. imperfect) datasets
• Experience deploying or maintaining models in a production or near-production setting is a plus

Domain Knowledge

• Any exposure to commodities, trading, financial markets, or energy systems is a strong plus, not a requirement
• A genuine will to learn a complex, fast-moving business model is essential

Soft Skills & Working Style

• High degree of autonomy — comfortable owning problems end-to-end with limited hand-holding
• Strong intellectual curiosity and drive to grow technically and domain-wise
• Clear communicator, able to work closely with traders and non-technical stakeholders
• Comfortable in a hybrid, project-driven environment with evolving priorities