Executive Director, Data & AI

Valtech

127d • $135,000 - $213,000

About The Position

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 proud of the work we do and the innovation we drive, our values of share, care and dare, a workplace culture that fosters creativity, diversity and autonomy, and our borderless, global framework, which enables seamless collaboration.

Requirements

• 10+ years in data/analytics/ML with 4+ years leading client-facing solution delivery; repeatedly trusted in executive rooms to land complex Data & AI programs.
• Demonstrated depth across GenAI/Agentic: tool-calling, retrieval patterns, prompt orchestration, evals/guardrails, cost/perf ops.
• ML/Advanced Analytics: experimental design, feature engineering, model selection, MLOps, monitoring.
• Data Foundations: lakehouse patterns, ELT/ETL, streaming, orchestration, governance/lineage.
• Hands-on familiarity with Azure + Databricks (Azure ML, Synapse/Fabric, Data Factory, Databricks Workflows/Model Serving) and/or GCP + Vertex/BigQuery (BigQuery, Dataflow, Vertex AI pipelines/endpoints).
• Excellent communication: can convert complexity into crisp decisions; strong written narratives and visual solution storytelling.
• Eligibility to work in Canada or the US; able to travel ~25–35% for key workshops, steering meetings, and go-lives.

Nice To Haves

• Experience operationalizing evaluation frameworks for GenAI (task suites, golden sets, automatic grading, red-teaming).
• Marketing analytics exposure (attribution/MMM, experimentation) and/or commerce, FS, or industrial verticals.
• Familiarity with data governance (e.g., Unity Catalog, lineage, fine-grained access), privacy engineering, and model risk practices.
• Contributions to thought leadership (talks, blogs, OSS) and to partner ecosystems (Azure/Databricks, Google/Vertex co-sell).
• Proven public voice in Data & AI (talks, publications, OSS, or analyst-cited frameworks).

Responsibilities

• Serve as the executive-facing Data & AI lead for priority accounts: frame business problems, shape hypotheses, define KPIs, and land value cases for AI/ML and agentic workflows.
• Translate between C-suite objectives and technical plans (governance, security, model risk, data contracts, SLAs).
• Co-own roadmaps that unify data foundations (ingest/model/serve), advanced analytics (forecasting/attribution/optimization), and GenAI (RAG/agents/tools) into a measurable value program.
• Design pragmatic architectures for agentic systems (tool-use, retrieval, planning/evaluation loops) that integrate with modern data stacks and application surfaces.
• Establish safe-by-default patterns: policy, PII handling, secret management, human-in-the-loop, evals/guardrails, cost/perf telemetry.
• Guide build vs. buy vs. assemble decisions across cloud services and partner ecosystems (Azure/Databricks; GCP/Vertex/BigQuery).
• Lead solution designs for MMM/MTA, forecasting, propensity, NLP/vision, and optimization; set modeling standards (feature stores, experiment design, drift/monitoring, MLOps).
• Review and raise the bar on notebooks, pipelines, and evaluation frameworks; insist on reproducibility, lineage, and documentation.
• Oversee pragmatic, governed data foundations (lakehouse, semantic layers, CDC/streaming, batch/real-time serving).
• Ensure architectures are right-sized for client constraints (security/compliance, cost, latency, vendor lock-in).
• Partner with Growth, Partnerships, and Vertical Leads to design and package market-ready offerings (discovery → pilot → scale) including scope, pricing guardrails, delivery blueprint, case studies, and ROI stories.
• Shape pursuits with POVs, demos, and reference architectures; support executive pitches with compelling value narratives and quantified outcomes.
• Evolve internal accelerators (conversational analytics, agentic eval harnesses, analytics workbenches) and coach teams on their use.
• Build repeatable playbooks (readiness assessment, risk/mitigation, success metrics), then enable Sales with one-pagers, proposal inserts, and talk tracks.
• Provide matrixed leadership to pods (DA/DE/DS/Analytics Eng) across 1–3 concurrent programs; mentor seniors/principals into client-credible leaders.
• Run delivery rituals that protect quality and pace (design reviews, red-team reviews, go-live checklists, incident postmortems).
• Drive a consistent cadence of external POVs (blogs, linkedin, bylines, whitepapers) and conference talks/webinars on agentic systems, GenAI safety/evals, and measurable AI value.
• Partner with Client Services and Legal to create case studies and win stories (KPIs, before/after).
• Collaborate with Microsoft/Databricks and Google/Vertex teams on joint content, solution spotlights, and marketplace listings.
• Define terminology, reference architectures, and maturity models that differentiate Valtech in Data & AI.
• Contribute to panels, roundtables, and analyst briefings; maintain an active professional presence (LinkedIn, podcasts).

Benefits

• Flexibility, with remote and hybrid work options (country-dependent).
• Career advancement, with international mobility and professional development programs.
• Learning and development, with access to cutting-edge tools, training and industry experts.
• Medical, dental, and vision insurance for you and your family, plus employer contributions to Health Savings Accounts.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Bachelor's degree
• Number of Employees: 5,001-10,000 employees