Senior Data Scientist

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 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.

• 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
• 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)
• 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

• 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

• 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

• 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

• 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

• 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)

• Hands‑on experience with at least one major cloud platform:
• Experience working with modern data and AI platforms (e.g., Azure ML / Azure AI, Databricks, or similar ecosystems)

• Experience working with complex, multi‑source datasets (e.g., transactional, behavioral, operational data)
• Ability to translate business problems into analytical frameworks

• 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