via indeed · 12 de junho de 2026 ·há 1 dia

Senior Data Scientist

Valtech Group
Lisboa Remote
Mais 126 vagas em Lisboa.
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Why Valtech? We’re advisors, visionaries, creative and techies. We embrace all things digital. We talk to each other. We have fun. We love our clients. We’re looking ahead • We are global


Why Valtech? We’re the experience innovation company \- a trusted partner to the world’s most recognized brands. To our people we offer growth opportunities, a values\-driven culture, international careers and the chance to shape the future of experience.

The opportunity

At Valtech, you’ll find an environment designed for continuous learning, meaningful impact, and professional growth. Whether you're pioneering new digital solutions, challenging conventional thinking or building the next generation of customer experiences, your work will help transform industries.

We are proud of:

  • The work we do and the innovation we drive

  • Our values of share, care and dare

  • A workplace culture that fosters creativity, diversity and autonomy

  • Our borderless, global framework, which enables seamless collaboration
The role

We are looking for an experienced Senior Data Scientist to drive advanced analytics, causal reasoning, and AI\-powered decision intelligence across multiple use cases within our AI portfolio. This role goes beyond traditional modeling and focuses on building production\-grade systems that combine predictive, causal, and generative AI capabilities to directly influence business outcomes.

You will work at the intersection of data science, machine learning, and GenAI, turning complex data into actionable insights, automated decisions, and intelligent workflows across domains such as marketing, operations, forecasting, and optimization.

This is not a purely retrospective analytics role. You will design and deploy systems that integrate experimentation, observational data, machine learning, and generative AI into real\-time or near\-real\-time decision\-making pipelines.

You will collaborate closely with data engineers, ML engineers, analysts, and platform teams, contributing to shared modeling standards and cross\-functional AI architecture.

Role responsibilities

Advanced Analytics \& Machine Learning

  • Develop and deploy machine learning models across use cases (forecasting, optimization, recommendation systems)

  • Apply statistical, predictive, and prescriptive modeling techniques to solve business problems

  • Build reusable modeling frameworks that can scale across multiple domains
Causal Inference \& Decision Intelligence
  • Design and implement causal inference methods (e.g., uplift modeling, experiments, quasi\-experimental methods)

  • Translate observational and experimental data into actionable business insights

  • Embed causal reasoning into decision systems that guide actions (e.g., optimization, prioritization, trade\-offs)
Generative AI \& Intelligent Systems
  • Integrate GenAI capabilities (e.g., LLMs, RAG pipelines, agent\-based systems) into data science workflows

  • Contribute to the development of intelligent agents and AI\-assisted decision\-making systems

  • Combine structured data models with unstructured data and GenAI outputs
Forecasting \& Optimization
  • Build forecasting models (time\-series, probabilistic, causal) to support planning and operations

  • Develop optimization approaches for resource allocation, scheduling, or campaign performance

  • Ensure models are explainable and actionable in business contexts
Production \& Platform Integration
  • Build and maintain production\-grade data science solutions

  • Collaborate with engineering teams to integrate models into scalable APIs and platforms

  • Ensure robustness, monitoring, and lifecycle management of deployed models
Cross\-Functional Collaboration
  • Partner with data engineering, analytics, and product teams to ensure data readiness and solution adoption

  • Review and validate modeling approaches across teams (forecasting, experimentation, ML)

  • Contribute to best practices in AI, ML, and data science within the organization
Must have qualifications

Data Science \& Statistical Expertise

  • Strong experience in machine learning, statistics, and applied data science

  • Experience with causal inference, experimentation, or decision science methodologies

  • Solid understanding of forecasting, optimization, or analytical modeling techniques
Technical Skills
  • Strong programming skills in Python and SQL

  • Experience building and deploying production\-ready data science or ML systems

  • Familiarity with model lifecycle management (training, deployment, monitoring)
Cloud \& Platform Experience (Key Requirement)
  • Hands\-on experience with at least one major cloud platform:

  • Azure (preferred), AWS, or GCP

  • Experience working with modern data and AI platforms (e.g., Azure ML / Azure AI, Databricks, or similar ecosystems)
Domain \& Data Experience
  • Experience working with complex, multi\-source datasets (e.g., transactional, behavioral, operational data)

  • Ability to translate business problems into analytical frameworks
Mindset
  • Strong problem\-solving skills with focus on business impact

  • Ability to translate complex models into actionable decisions

  • Strong collaboration and communication skills across technical and business teams
Nice to have qualifications
  • Deep experience in marketing analytics, attribution, or campaign measurement

  • Hands\-on experience with:
+ Uplift modeling, geo experiments, synthetic control
+ Marketing Mix Modeling (MMM)
  • Experience with GenAI frameworks (e.g., LangChain, LangGraph, RAG architectures, agent frameworks)

  • Familiarity with data engineering tools (e.g., Spark, Airflow, dbt)

  • Experience with platforms such as Snowflake, Fabric, or BigQuery

  • Exposure to advanced time\-series methods and probabilistic forecasting

  • Experience working in Agile, product\-led, or consulting environments
Commitment to reaching all kinds of people

We design experiences that work for all kinds of people \- and that starts with our own teams. At Valtech, we’re intentional about building an inclusive culture where everyone feels supported to grow, thrive and achieve their goals. No matter your background, you belong here. Explore our Diversity \& Inclusion site to see how we’re creating a more equitable Valtech for all.

The benefits

This is a position based in Portugal.

Beyond a competitive compensation package, we offer:

  • Flexibility, with remote and hybrid work options (country\-dependent)

  • Career advancement, with international mobility and professional development programs

  • Learning and development, with access to cutting\-edge tools, training and industry experts
Our benefits are tailored to each location. Your Talent Partner will provide full details during the hiring process.

Your application process

Once you apply, our Talent Acquisition team will review your application. Your CV should cover key information on relevant experiences and expertise. We do not require information such as age, gender, marital status, or a headshot in your application. We review all candidates based on skills, experience, and potential.

  • ️ Beware of recruitment fraud!
We are committed to inclusion and accessibility. If you need reasonable accommodations during the interview process, please either indicate it in your application or let your Talent Partner know.

About Valtech

Valtech is the experience innovation company that exists to unlock a better way to experience the world. By blending crafts, categories, and cultures, we help brands unlock new value in an increasingly digital world.

At the intersection of data, AI, creativity, and technology, we drive transformation for leading organizations, including L’Oréal, Mars, Audi, P\&G, Volkswagen Dolby, and more.

At Valtech, we don’t just talk about transformation. We make it happen. Our people are the heart of our success, and we foster a workplace where everyone has the support to thrive, grow and innovate.

Are you ready to create what’s next? Join us.

O mercado para este tipo de cargo

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