Valtech

Data Scientist

• Drive advanced analytics, causal reasoning, and AI-powered decision intelligence across multiple use cases within our AI portfolio
• Build production-grade systems that combine predictive, causal, and generative AI capabilities
• Design and deploy systems that integrate experimentation, observational data, machine learning, and generative AI into real-time or near-real-time decision-making pipelines
• Collaborate closely with data engineers, ML engineers, analysts, and platform teams
• 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

Senior Data Scientist

Data Engineer

• Design and implement scalable data platforms and pipelines across cloud environments (Azure/Fabric, AWS, GCP, Databricks, Snowflake)
• Deliver high-quality datasets that support analytics, machine learning, causal modeling, and optimization systems
• Design scalable logical and physical data models for analytical and operational use cases
• Apply modern architecture patterns including event-driven and streaming architectures
• Establish strong data observability, including monitoring of data freshness, pipeline reliability, and SLA adherence
• Enable data serving layers (APIs, feature inputs, analytical endpoints) to support downstream systems

Senior Data Engineer

• Design and implement scalable data platforms and pipelines across cloud environments
• Develop reliable batch, streaming, and near-real-time pipelines using technologies such as Spark and Delta Lake
• Build ingestion, transformation, and curation workflows for both structured and unstructured data
• Implement modern data architectures including lakehouse patterns and medallion layering
• Deliver high-quality datasets that support analytics, machine learning, causal modeling, and optimization systems
• Enable data pipelines for GenAI use cases
• Design scalable logical and physical data models
• Orchestrate workflows using tools such as Airflow, dbt, Lakeflow, or equivalents
• Apply modern architecture patterns including event-driven and streaming architectures
• Establish strong data observability, including monitoring of data freshness, pipeline reliability, and SLA adherence
• Enable data serving layers to support downstream systems

• Design and implement scalable data platforms and pipelines across cloud environments (Azure/Fabric, AWS, GCP, Databricks, Snowflake)
• Developing reliable batch, streaming, and near-real-time pipelines
• Ensure adherence to best practices in data governance, lineage, quality, and access control (RBAC/ABAC)
• Establish strong data observability, including monitoring of data freshness and pipeline reliability
• Work closely with data scientists, ML engineers, analysts, and business stakeholders to translate requirements into robust data solutions

Procurement

• Lead the end-to-end sourcing cycle for Professional Services and Consulting — from supplier identification and RFQ through to negotiation, contract execution, and renewal management.
• Build and manage a preferred supplier panel for consulting and professional services, establishing role-based rate cards and standard commercial terms across the category.
• Negotiate contract pricing, terms, and conditions directly with suppliers — optimizing for cost, quality, and risk mitigation in collaboration with Legal, Data Privacy, and Cybersecurity.
• Enable efficient and effective purchase services with a focus on business value, on-time delivery, and cycle time.
• Manage the portfolio of active agreements including scope, pricing, amendments, and renewals and coordinate intake requests for the category, delivering a seamless experience for internal stakeholders.
• Drive portfolio consolidation projects that reduce supplier fragmentation and deliver measurable cost savings, Identify and leverage value opportunities within the portfolio, including volume leverage, multi-year commitments, and cross-business unit consolidation.
• Oversee the sourcing cycle, handle tenders, and maintain strong relationships with suppliers, engaging effectively with multiple stakeholders.
• Benchmark supplier rates and market positioning against external references, providing credible commercial challenge to both suppliers and internal stakeholders.
• Maintain strong relationships with key internal stakeholders including delivery leaders, Finance, Legal, and senior management across NA & EMEA.
• Evaluate and continuously improve procurement processes within the category, contributing to playbook development and governance standards.
• Contribute to the broader procurement transformation roadmap, including system implementation, policy rollout, and AI-assisted tooling adoption.

Procurement Project Lead

• Design, build, and maintain reliable and scalable data pipelines, primarily leveraging SQL
• Develop and optimize complex queries to support analytics and reporting needs
• Ensure data accuracy, consistency, and quality across multiple data sources
• Partner with stakeholders to translate business questions into data solutions
• Support experimentation frameworks, including A/B testing and data validation
• Work with analytics teams to deliver datasets used in dashboards and reporting tools (e.g., Metabase or similar)
• Communicate insights effectively through data storytelling, tailoring messages for non-technical audiences
• Collaborate with cross-functional teams in a client-facing consulting environment
• Contribute to best practices in data modeling, documentation, and governance

Data Engineer – Mid-Level

Project Manager

• Oversee the delivery of brand marketing initiatives including analyst relations, industry awards, PR campaigns, and thought leadership programs.
• Partner with external PR agencies and internal stakeholders to coordinate media outreach and maintain relationships with journalists and analysts.
• Manage awards submission calendars, content creation, and cross-team inputs to ensure deadlines are met.
• Support the creation and dissemination of press releases, case studies, and brand storytelling assets.
• Define project scope, objectives, deliverables, and timelines in collaboration with stakeholders and the marketing teams.
• Develop and manage detailed project plans, schedules, and budgets for brand marketing campaigns.
• Track progress, manage risks, and resolve project roadblocks.
• Coordinate cross-functional input from design, content, digital, and product marketing teams.
• Keep global comms calendar up to date, working closely with Regional and Functional leaders.
• Serve as the primary point of contact for project updates across marketing leadership, PR agencies, and analyst firms.
• Manage expectations and alignment with internal and external stakeholders.
• Monitor and report on the impact of PR, awards, and analyst relations activities.
• Provide insights and recommendations to improve future brand initiatives.
• Identify opportunities for process improvements in planning and execution.

Marketing Project Manager, Brand and Comms

Designer

• Lead Service Design and Customer Experience (CX) initiatives, considering the end-to-end customer journey from acquisition through ongoing relationship management.
• Compile, organize, and analyze existing inputs such as:
• Voice of the Customer (VoC)
• historical surveys and customer feedback
• internal studies and previous evaluations
• Plan and facilitate customer listening initiatives with customers and stakeholders, including:
• interviews
• qualitative and quantitative research
• Map customer journeys, identifying:
• pain points
• process bottlenecks
• opportunities for improvement and optimization
• Support the definition and evolution of the desired experience model, considering:
• unified vs. segmented experience strategies
• differentiation by customer profile and stage in the journey
• Create and structure:
• prioritization matrices
• initiative timelines with short-, medium-, and long-term actions
• Support initiatives aimed at strengthening and promoting a customer-centric culture across the organization.
• Collaborate cross-functionally with internal teams, monitor initiative execution, and ensure quality, consistency, and strategic alignment across deliverables.
• Demonstrate openness to leveraging AI-driven tools and emerging technologies to increase productivity, insight generation, and decision-making, applying critical thinking and sound judgment in their use.

Senior CX Designer

Content Writer

• Writing and optimizing SEO articles.
• Creating product descriptions, categories, and landing pages.
• Developing buying guides and educational content.
• Optimizing content with a focus on SEO and basic AI Search.
• Researching search trends for content planning.
• Using AI tools for content research and optimization.
• Managing multiple formats and accounts simultaneously.

Senior Data Scientist

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Procurement Project Lead

Data Engineer – Mid-Level

Data Engineer – Mid-Level

Marketing Project Manager, Brand and Comms

Senior CX Designer

Junior Content Writer