AI Expert

Versuni (formerly Philips Domestic Appliances); Amsterdam; On-site; EUR 90,000 - 150,000; Full time

Benefits offered by this job

Work-from-home allowances

Phone allowances

Product discounts on Versuni products

Job summary

Versuni, a leader in consumer appliances, seeks an AI Expert to shape opportunity spaces through advanced analytics. You’ll transform mixed-source data into quantified innovation opportunities and build evidence-based business cases for early R&D decisions.

The role emphasizes predictive and causal modelling, GenAI enablement, and experimentation to de-risk portfolios. Strong collaboration with cross-functional teams is essential.

Qualifications

• 5–8+ years in applied data science (innovation, product, growth or research).
• Master’s/PhD in Data Science, Statistics, Econometrics, CS, Applied Math or similar.
• Experience with mixed-source data (behavioral, survey, telemetry, reviews, market data).
• Background in consumer products/electronics or adjacent innovation sectors preferred.

Responsibilities

• Identify and synthesize mixed-source data to uncover unmet needs, behaviors and trends.
• Build segmentation, cohorts, journeys and JTBD analyses explaining usage.
• Quantify opportunity size, growth and strategic fit.
• Integrate qualitative and quantitative research loops.
• Translate external disruption signals into innovation cues.

Skills

ML & Statistics

Experimentation

Storytelling

Data-driven decision making

Business framing

Education

Master’s/PhD in Data Science or related field

Tools

Python

PySpark

SQL

Streamlit/FastAPI

GenAI tooling

Job description

About the role

As an AI Expert in the Disruptive Innovation team, you build and operate the opportunity‑discovery analytics capability for our global appliances portfolio. You turn mixed‑source consumer, usage and market data (panels, reviews, e‑commerce, social, research, telemetry) into quantified opportunity spaces, causal‑grade business cases and decision‑ready evidence.

This is forward‑looking, opportunity‑stage analytics (not product analytics): identifying unmet needs, validating early hypotheses and shaping innovation portfolios with rigorous, evidence‑based insight.

Impact

• Translate behavior & usage data into quantified innovation spaces and disruption theses
• Provide causal evidence influencing early‑stage R&D and investment decisions
• Accelerate learning via experiments and qual‑quant integration
• De‑risk innovation by quantifying uncertainty and assumptions

Key responsibilities

Opportunity discovery & analytics

• Identify and synthesize mixed‑source data to uncover unmet needs, behaviors and trends
• Build segmentation, cohorts, journeys and JTBD analyses explaining usage
• Quantify opportunity size, growth and strategic fit
• Integrate qualitative and quantitative research loops
• Translate external disruption signals into innovation cues

Predictive, causal & GenAI modelling

• Develop predictive and causal models (propensity, adoption, churn, latent needs)
• Apply causal methods (DiD, synthetic controls, IV, uplift/ML) for decision‑making
• Build scenario and portfolio models for simulations/digital twins
• Use GenAI/LLMs to mine unstructured data with human‑in‑loop interpretation
• Maintain reusable analytical assets (models, code, segmentations)

Experimentation & business cases

• Design and run experiments (A/B, multivariate, conjoint, MVP tests)
• Translate results into clear opportunity narratives (size, drivers, risks)
• Build quantitative business cases (demand, pricing, adoption, cannibalization)
• Identify bias and ensure robust evidence quality

Data products & tooling

• Build lightweight tools and GenAI‑enabled apps for self‑serve exploration
• Productionize pipelines and workflows (Python, SQL, orchestration)

Collaboration & storytelling

• Partner with concept, research and technical teams on hypotheses and insights
• Align with commercial, marketing and product teams on data and positioning
• Communicate insights via clear narratives for technical and business audiences
• Promote experimentation and evidence‑based ways of working

The skills and knowledge you’ll bring

Education

• Master’s/PhD in Data Science, Statistics, Econometrics, CS, Applied Math or similar (or equivalent experience)

Experience

• 5–8+ years in applied data science (innovation, product, growth or research)
• Proven delivery of quantified opportunity spaces/business cases adopted by leadership
• Experience with mixed‑source data (behavioral, survey, telemetry, reviews, market data)
• Background in consumer products/electronics or adjacent innovation sectors preferred

Technical skills

• Strong ML, statistics and experimentation (time‑series, survival, propensity, conjoint)
• Hands‑on causal inference (DiD, synthetic controls, IV, causal graphs)
• Strong Python/PySpark and SQL
• Experience building data tools/apps (APIs, Streamlit, FastAPI or similar)
• Experience with unstructured data and GenAI/LLMs
• Proficiency in BI/visualization for insight storytelling

Analytical & business skills

• Strong problem framing and strategic thinking
• Business case fluency (demand, pricing, unit economics, regulation, sustainability)
• Comfortable with uncertainty; explicit on assumptions and scenarios
• Able to manage multiple priorities in exploratory environments

Competencies

• Strong storytelling for technical and non‑technical audiences
• Highly collaborative; integrates qualitative and quantitative insights
• Strong consumer empathy and curiosity
• Intellectually honest; challenges assumptions constructively
• Proactive, self‑driven and entrepreneurial

Background

• Preferred: appliances, consumer electronics, connected products, innovation‑driven sectors
• Also relevant: FMCG innovation, behavioral science, product strategy, growth analytics (discovery‑focused)
• Less suited: purely BI/reporting, performance marketing analytics or pure data engineering roles

What we’ll give you in return

• Internationally competitive base salary, benchmarked against global industry and market leaders.
• Performance‑based Annual Incentive Program, rewarding those who dare and achieve more.
• Top‑of‑the‑market pension plan with the opportunity for higher employee contributions.
• Work‑from‑home and phone allowances to support your home office setup and business connectivity.
• Balanced office‑based working with a strong focus on in‑office collaboration, plus flexibility to work from home based on team needs and individual circumstances.
• Work from abroad for up to 30 days per year.
• Structured holiday policy, including defined care days, enhanced maternity/paternity leave, and a capped option to purchase additional leave days annually.
• Special health insurance plan for Versuni employees with convenient conditions when signing up with our partner insurance.
• Product discounts on all Versuni products sold under the Philips brand and our other brands.
• High‑growth environment, offering exciting learning and career development perspectives beyond your first role.
• Inclusive working culture and family spirit; we embrace our international community and diversity as a competitive advantage.