Analytics leadership · transformation · commercial impact

Build the analytics function that the business can actually run on.

I connect strategy, multidisciplinary project teams of 15–25, trusted metrics and hands-on delivery. The result is not another dashboard estate: it is a clearer operating system for decisions across commercial performance, payments, fraud, customer behaviour and AI-enabled workflows.

Primary fit: Head of Analytics · Head of BI / Insights · Analytics Manager / Senior Manager · Data & Analytics Transformation Lead · Commercial, Fraud or Payments Analytics Lead.
Adjacent fit: selective Head of Digital or Digital Transformation roles where the remit is centred on data, CRM, measurement, operating-model change and AI adoption.
Looking for project work rather than a hire? See consulting & fractional engagements →

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15+years across analytics, BI and commercial systems

15–25people in multidisciplinary project teams

7markets aligned through one KPI framework

~20% · ~10%marketing uplift and payment-cost reduction

What I lead

Analytics strategy & operating model

Define which decisions matter, who owns the metrics, how data products are prioritised and how insight becomes an operating rhythm.

strategyroadmapsgovernance

Teams & cross-functional delivery

Lead project teams of 15–25 across analysts, outsourced developers, project managers, technical specialists, suppliers and client-side owners; set priorities, governance, quality standards and accountability.

peopledeliverystandards

Executive decision systems

Turn fragmented reporting into common definitions, commercial narratives, scenario choices and clear actions for senior leadership.

board insightKPI systemsadoption

AI-enabled transformation

Introduce AI as a controlled analytical multiplier, with human approval, validation, explicit failure modes and verification-first workflows.

AI workflowsQAhuman in loop

Leadership evidence

TUI · Multi-market analytics transformation

Designed and led rollout of a unified campaign-performance data and KPI framework across seven countries. Aligned markets around shared definitions, integrated sources and executive reporting.

Outcome: approximately 20% group-wide uplift in campaign performance.

UFS Consulting · Transformation teams of 15–25

Consistently led multidisciplinary project teams combining outsourced developers, project managers, analysts, technical specialists and client-side owners. Directed programmes spanning analytics transformation, KPI-system rollout, card-acquiring optimisation, payments-operating-model improvement, and fraud-prevention and fraud-analytics implementation for a large hotel network.

Leadership scope: owned delivery from diagnosis and business case through roadmap, workstreams, supplier coordination, adoption and verified outcome. The wider portfolio included approximately EUR30m invoiced in one year across multiple engagements, including subcontracted work.

Betfair · Payments and margin decisions

Owned forecasting, budgeting and KPI reporting used to steer card-processing operations, working across Payments, Finance, Risk and Operations.

Outcome: approximately 10% processing-cost reduction and correction of a referral-fee classification issue affecting reported margin.

Nestlé · Direct people leadership

Managed a regional team of 15 using clear KPIs, coaching, commercial negotiation and structured market analysis.

Outcome: consistent target delivery and an early foundation in accountable team leadership.

What colleagues and leaders say

Public LinkedIn recommendations from former managers and senior colleagues in payments and iGaming.

“Sergejs was in my data/support team at Betfair. He was a joy to work with, providing insightful data with a great narrative. Sergejs is always happy to try new things and work outside of his comfort zone. He would be a great addition to any team.”

Phil Rivers · Group COO, ClearBankSenior to Sergey at Betfair

“Sergejs and I worked together at Betfair several years ago. Sergejs was always very professional, and it was a pleasure to work with him!”

Rahul Das · iGaming & ePayments professionalManaged Sergey directly at Betfair

Verify these on LinkedIn →

How I would approach the first 90 days

Days 1-30 · Diagnose

Map business decisions, stakeholders, metric conflicts, team capacity, data trust and current delivery bottlenecks. Establish where value is leaking and where confidence is weakest.

Days 31-60 · Align

Agree a small set of priority outcomes, owners and common definitions. Build the delivery roadmap, governance rhythm and visible quality bar with the team.

Days 61-90 · Prove

Deliver one or two high-value decision products end to end, measure adoption and business effect, and use the evidence to scale the operating model.

Technical depth without hiding behind tools

SQL and BigQuery data modelling
Looker / Looker Studio, Tableau and Power BI
Alteryx transformation and predictive workflows
KPI governance, semantic/reporting layers
Validation, reconciliation and anomaly investigation
Payments, fraud, CRM and customer behaviour
Forecasting, budgeting and commercial decision models
RFPs, supplier negotiation and outsourcing

The leadership proposition is evidence-led: commercial impact, transformation, teams, stakeholder influence and delivery. Tools support that proposition; they do not replace it.

Research edge

Independent AI-safety research

CRepair studies detect-repair-verify loops in long-horizon AI agents through DOI-linked preprints, open benchmark scenarios, public code and cross-model replication.

Why it matters commercially

The research brings a disciplined approach to AI adoption: test the failure modes, require verification, retain human judgement and measure whether recovery actually worked.

Research profile CRepair explainer ORCID

Selected sanitised cases

Public analytics case study