Valtech

Valtech

Valtech is a global business transformation company specializing in technology, marketing, and experience design to help clients innovate, connect with consumers, and optimize ROI.

Professional Services
5K-10K
Founded 1993

Description

  • Contribute to production readiness through monitoring, incident response support, and operational runbooks.
  • Conduct root-cause analysis of production issues that lead to adverse model outputs.
  • Design, build, and optimize marketing mix models, attribution models, and other econometric or causal models.
  • Select and implement machine learning models for time-series forecasting, supply-chain optimization, and marketing performance use cases.
  • Write well-tested, maintainable code in existing object-oriented Python codebases.
  • Analyze large-scale raw datasets to deliver impact for enterprise clients while maintaining scientific rigor.
  • Engineer data pipelines and data products that support data-driven marketing and business decisions.
  • Communicate analytical insights clearly through visual, intuitive presentations for marketing, product, and executive audiences.
  • Create 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 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 or ML models using marketing or media data.
  • 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, including precision/recall, MAPE, ROI, incrementality, and 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.
  • Experience contributing to packaged software libraries in open-source or industry repositories.
  • Proficiency in visualization and reporting tools such as Tableau and Power BI, or programmatic visualization libraries such as R ggplot2, Python matplotlib/seaborn/bokeh, or JavaScript D3.
  • Proficiency in Looker and SQL-first analytical storytelling, with the ability to produce decision-ready visuals and narratives.
  • Proficiency scripting in a UNIX environment.
  • Proficiency in big data environments and tools such as Spark, Hive, Impala, or Pig.
  • Proficiency with cloud architecture components across AWS, Azure, or Google.
  • Proficiency with GCP architecture components relevant to secure analytics products, including 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-end and back-end web application development stacks and frameworks, including JavaScript, HTML, CSS, React, Vue, or AngularJS, as well as REST or GraphQL API design and library development.
  • Experience leading and managing technical data, analytics, or machine learning projects.

Benefits

  • Competitive compensation package.
  • Remote and hybrid work options, depending on country.
  • International mobility and career advancement opportunities.
  • Professional development programs.
  • Access to cutting-edge tools, training, and industry experts.
  • Inclusive, values-driven culture with support for growth and innovation.

Interested in this position?

Apply directly on the company website

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