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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.
Job Responsibility:
Contribute to production readiness through monitoring
incident response support
and operational runbooks to meet agreed service levels
Conduct root-cause analysis of production issues that lead to adverse model outputs
Design
build
and optimize marketing mix models (MMM)
attribution models
and other econometric or causal models using marketing data
Select and implement appropriate machine learning models for time-series forecasting
supply-chain optimization
and marketing performance use cases
Contribute well-tested
maintainable code to existing object-oriented Python codebases
Analyze raw
large-scale datasets to deliver meaningful impact for enterprise clients while maintaining scientific rigor
Engineer data pipelines and data products that enable stakeholders to make informed
data-driven marketing and business decisions
Communicate analytical insights in a clear
intuitive
and visually compelling manner for marketing
product
and executive audiences
Create highly visual and interactive dashboards using Tableau
Power BI
Looker
or custom web applications
Conduct deep-dive analyses and design KPIs to measure marketing effectiveness
ROI
incrementality
and business growth
Engineer data infrastructure
libraries
and APIs supporting BI
ML
and marketing analytics pipelines
Architect cloud data platform components that enable scalable analytics and modeling solutions
Build and manage project timelines
dependencies
and risks
Gather stakeholder requirements and perform technical due diligence to design pragmatic
data-driven marketing and business solutions
Requirements:
Hands-on experience with GCP services used in production analytics environments, including BigQuery, Vertex AI, Looker, Pub/Sub, Cloud Functions, Cloud Storage, and Cloud Run (or equivalent deployment/runtime patterns)
Proven experience building marketing mix models, attribution models, or other statistical/ML models using marketing or media data (e.g., paid media, campaign performance, digital channels, or customer journeys)
Proven industry experience developing predictive or inferential statistical models or a Master’s/PhD in a quantitative field such as Engineering, Mathematics, Statistics, Computer Science, or related disciplines
Deep understanding of causal inference, time-series analysis, or econometric techniques as applied to marketing analytics
Experience applying statistical and machine learning libraries effectively to real-world business and marketing problems
Proficiency in SQL, Python, and/or R, with the ability to execute end-to-end data ingestion through insight generation
Experience defining and reporting model performance and business impact metrics (e.g., precision/recall, MAPE, ROI, incrementality), including documented backtesting
Experience delivering production model artifacts such as model cards, registry updates, confidence intervals, and guardrail-aware recommendations
4+ years of experience in similar data science, marketing analytics, or advanced analytics roles
Advanced English proficiency
Nice to have:
Experience contributing to packaged software libraries in open-source or industry repositories
Proficiency in visualization/reporting tools such as Tableau and PowerBI or programmatic visualization library such as R ggplot2, Python matplotlib/seaborn/bokeh, Javascript D3.
Proficiency in Looker and SQL-first analytical storytelling
ability to produce decision-ready visuals and narratives for marketing and executive audiences
Proficiency scripting in UNIX environment
Proficiency in big data environments and tools such as Spark, Hive, Impala, Pig, etc.
Proficiency with cloud architecture components (AWS, Azure, Google)
Proficiency with GCP architecture components relevant to secure analytics products (IAM/service accounts
RBAC-aware data access
deployment and observability patterns)
Proficiency with data pipeline software such as Airflow
Luigi
or Prefect
Ability to turn raw data and ambiguous business questions into distilled findings and recommendations for action
Proficiency in front and back-end web application development stacks and frameworks (Javascript
HTML
CSS
React/Vue/AngularJS) including API design (REST/GraphQL) and library development
Experience leading and managing technical data/analytics/machine learning projects
What we offer:
Flexibility
with remote and hybrid work options (country-dependent)
Career advancement
with international mobility and professional development programs