For scaling companies building data and AI leverage
Product Leader for AI-Native Data Platforms
I help scaling companies turn complex data workflows into reliable platforms, governed access, analytics, automation, and AI-powered decisions.
- Amazon
- ex-Ancestry
- Advisor.energy co-founder
- Data, AI, governance, analytics
Proof and metrics
- Startup-to-enterprise product range
- 400% ROI from workflow modernization
- 50-60% platform cost reduction
- 100+ data pipelines
- 20+ engineer data teams
What I build
Data, AI, and workflow products with practical operating leverage
I work where data, workflow, governance, and AI become product systems: the places where scaling companies need leverage, clarity, and practical operating rhythm.
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Governed data access and sharing
Product systems that make data easier to find, trust, permission, and use across teams.
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AI/ML automation and decision workflows
Workflow automation that improves decision quality while keeping confidence, evidence, and human review visible.
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Analytics infrastructure and KPI systems
Metric pipelines, reporting foundations, and operating rhythms that connect product work to business outcomes.
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APIs, integrations, and platform adoption
Internal and external platform capabilities designed around adoption, reliability, and repeatable use.
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Lightweight operating systems for product and data teams
Just enough planning, prioritization, and delivery discipline for the company stage.
Selected work
Startup product building, data platforms, automation, and analytics
Selected work shows the range: startup product building, data-platform modernization, high-scale automation, and predictive analytics products.
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Startup builder
B2B SaaS and ML analytics at Advisor.energy
Founder/operator proof for scaling-company product work.
- Converted complex market data into ML-powered insights.
- Built self-service workflows for customer-facing decisions.
- Balanced product ownership, data science, and customer value.
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Scale modernization
Data platform modernization at ex-Ancestry
Data-platform and analytics scale proof.
- Modernized platform capabilities across migration, governance, and KPI pipelines.
- Improved cost, SLA performance, and delivery discipline across data teams.
- Scaled analytics and data operations across 100+ pipelines and 20+ engineer teams.
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High-scale systems
Data-sharing and automation at Amazon
Current scale proof across high-stakes data workflows.
- Works on governed access, confidential workflows, automation, and predictive analytics.
- Connects reliability, cost, compliance, and business outcomes.
- Shows product decisions across reliability, cost, governance, and measurable outcomes.
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Technical foundation
Predictive analytics and simulation products at SLB
Technical foundation in applied math and global product strategy.
- Worked on predictive analytics and numerical simulation products.
- Supported complex technical decision-making across global markets.
- Built fluency across product strategy, GTM, and technical workflows.
Portfolio Lab
Product strategy, teardowns, and working prototypes
Portfolio Lab makes Niko's product thinking tangible through concise strategy memos, product teardowns, diagrams, and interactive prototypes for AI-native data products.
- Strategy memo
Data Governance Product Strategy Memo
Minimum viable governance for scaling companies.
View artifact - Teardown
AI-Native Data Catalog Teardown
Where AI helps metadata, lineage, search, policy interpretation, and quality triage.
View artifact - Interactive prototype
Agentic Data Quality Assistant
Mock incident workflow with evidence, confidence, human approval, and audit trail.
Open prototype
Product principles
How I approach AI-native data products
- Govern the data before scaling the model.
- Treat platform adoption as the product, not a launch afterthought.
- Use AI to improve workflow accountability, not hide uncertainty.
- Measure business outcomes, not feature volume.
- Bring just enough operating discipline for the company stage.
About
Applied technical depth, founder range, and scaled product judgment
Niko started in applied mathematics and numerical simulation, building systems that translated complex physical and business data into better decisions. That thread has carried through his work as a founder, startup product builder, and product leader at SLB, Advisor.energy, ex-Ancestry, and Amazon.
His strongest work sits where product strategy, data architecture, governance, and business outcomes meet. He helps teams turn ambiguous data and AI opportunities into practical product systems: governed access, analytics infrastructure, automation, platform adoption, and measurable outcomes.
Contact
Relevant product leadership, data, AI, and advisory conversations
For product leadership roles, data and AI platform opportunities, or relevant advisory conversations, contact Niko by email or LinkedIn.