Valtech

Data Scientist

• Drive advanced analytics, causal reasoning, and AI-powered decision intelligence across multiple use cases
• Build production-grade systems that combine predictive, causal, and generative AI capabilities
• Turn complex data into actionable insights, automated decisions, and intelligent workflows
• Design and deploy systems that integrate experimentation, observational data, machine learning, and generative AI
• Collaborate closely with data engineers, ML engineers, analysts, and platform teams

Senior Data Scientist

• Drive advanced analytics, causal reasoning, and AI-powered decision intelligence across multiple use cases within our AI portfolio.
• Work at the intersection of data science, machine learning, and GenAI, turning complex data into actionable insights, automated decisions, and intelligent workflows.
• 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, 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.

• 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

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.

Junior Content Writer

• manage the scope, budgets, and the timeline of e-commerce software development projects;
• manage client communications for multiple large-scale development efforts;
• manage project documentation & maintain the related knowledge base;
• assign work tasks, manage workload and properly allocate work efforts between project team members;
• motivate project team members, encourage and support productive work performance, and facilitate team collaboration;
• anticipate the client’s needs, investigate and propose alternative technical solutions to clients through internal and external consulting and technical research;
• consistently deliver high-quality customer service;
• expand and enhance your own expertise in the e-commerce professional services domain, and be aware of global trends in the online retail & professional software delivery industry;
• conduct performance evaluations of project team members, provide employee performance feedback to department heads, and provide input for employee career development planning.

Software Engineer

• Lead Flutter mobile app development across Android / iOS.
• Focus on best engineering practices for quality, clean code, testing & observability.
• Architect scalable, maintainable, and performant mobile solutions.
• Mentor and guide Flutter developers; conduct code reviews.
• Collaborate with product, design, and backend teams.
• Ensure code quality, testing, and CI/CD integration.
• Stay updated with Flutter/Dart trends and best practices.
• Manage technical risks and project timelines.

Lead Flutter Engineer

Frontend Engineer

• Design and implement responsive, high-performance web interfaces using Angular.
• Translate UX/UI designs from Figma into clean, maintainable, and scalable code.
• Ensure consistency in UX across platforms, components, and user flows.
• Collaborate with UX designers to refine user journeys and improve usability.
• Develop reusable UI components and maintain a scalable design system.
• Optimize applications for performance, accessibility, and cross-browser compatibility.
• Work closely with backend developers (Node.js) to integrate APIs and services.
• Participate in code reviews and enforce frontend best practices.
• Continuously improve UI/UX standards, patterns, and design consistency.
• Mentor junior developers and contribute to team knowledge sharing.

Senior Data Scientist

Senior Data Scientist

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

Project Manager

Lead Flutter Engineer

Senior FrontEnd UX/UI