Principal Product Designer for financial and AI decision systems. 12+ years across UBS, CME/NYMEX, Refinitiv, KKR, Jupiter, and Tassat. I turn high-stakes workflows into auditable, buildable products.
Across climate risk, options trading, workforce planning, clinical benchmarking, and talent mapping, the same failure repeats: dense model output is easy to misread, and the consequence lands in capital, risk, headcount, hiring, and decisions that are expensive to reverse. That misread is the problem this portfolio is built against.
I design institutional decision-intelligence systems that expose the mechanism behind the answer, keep uncertainty legible, and make the next action auditable by design. I accelerate engineering by using AI coding agents to turn strategy into functional React and TypeScript prototypes, so teams build from working logic, not static specs. In FDE terms, I hold the Echo seat: forward deployed product discovery, embedded with the people who own the decision.
Role, approach, and outcome
Reveal the mechanism
I design decision interfaces that show what drives the recommendation, which assumptions matter, and where the model stops being certain.
Keep uncertainty visible
I do not flatten probabilistic systems into fake certainty. Range, confidence, and consequence stay legible in the interface.
Support auditable action
Each screen becomes a decision artifact a portfolio manager, operator, or staffing lead can defend in a real review.
Experience & Scale
12+ years designing decision interfaces across capital markets, climate risk, and enterprise data products, as both a hands-on individual contributor and a design leader who builds and runs teams, systems, and user research practice.
Principal Product Designer
July 2026 – Present
Head of Product Design & UX
October 2025 – July 2026
AI-Augmented Product Designer
2024 – 2025
Product Designer (contract)
2024
Independent Design Consultant
2023 – 2024
UX Designer, Design Systems & Data Visualization
2022 – 2023
Independent Design Consultant
2020 – 2022
Senior Product Designer
2019 – 2020
Senior UX Designer
2010 – 2019
Where Misreading Breaks Decisions
The through-line in this portfolio is not the industry. It is what happens when people misread dense information under pressure. The value proposition is direct: the stakes of misreading data are measured in capital, risk, and decisions that cannot be undone.
Climate Risk
22,000 probabilistic data points per asset can turn into incorrect investment calls. The portfolio solution is to keep uncertainty visible in the interface.
Options Trading
Traders misread the volatility surface and commit capital on the wrong read. The portfolio solution is linked decision geometry across slice, grid, spread, and strategy views.
Workforce Planning
Staffing uncertainty gets flattened into false precision and headcount is misallocated. The portfolio solution is an allocation model that turns uncertainty into actionable moves.
Clinical Benchmarking
Exception patterns are missed and care quality risk stays hidden too long. The portfolio solution is an exception-led command center.
Talent Mapping
Candidates are misread because expertise is treated like a list instead of a network. The portfolio solution is graph navigation that makes expertise topology visible.
Finance Operations
AI-flagged exceptions get rubber-stamped or ignored and audit defensibility erodes. The portfolio solution is a reviewer workspace that keeps model uncertainty visible and welds each verdict to an immutable audit artifact.
Selected Work
Similarity Is Not Correctness
Agentic AI can retrieve something close enough to sound right and wrong enough to cost money. This case maps failure modes, stress-tests stacked gates, and ships Action Ledger: an auditable prototype for governed retrieval and reversible autonomy.
Core decision: calibrate one reversible, self-auditing boundary instead of stacking gates; traded throughput for accountability.
Incline Trust
A reviewer workspace for an AI-driven corporate spend and payments platform. The model flags expense and vendor exceptions; the interface makes that model legible enough that a controller can accept, adjust, or reject each call under a tunable confidence band, then emit an immutable, auditable record without leaving the page.
Core decision: rank the inbox by confidence band, not point score; traded a familiar ranked list for a queue that surfaces variance, not just severity.
Volatility Surface
A linked decision-intelligence workspace for options traders. It holds one market context across surface, slice, grid, spread, and strategy views, with a stress-calibrated value-at-risk gauge, so the desk reads the field correctly by design.
Core decision: one shared market context across 5 views instead of per-view state; traded screen density for coherence.
More work
Climate-risk disclosure UI for Tier 1 banks and insurers, wired to live climate models.
Signal triage, company context, notes, and follow-ups unified into one coverage workflow.
Enterprise talent mapping that makes the topology of expertise visible across a 200-person pool.
Exception-led clinical benchmarking command center across 101 physicians and 4 years of data.
iOS and Android clinical prototype sharing one state machine to catch logic errors pre-build.
Founder-built workforce planning product turning staffing uncertainty into actionable operating moves.
About
Principal product designer with 12+ years building interfaces where the stakes of misreading data are measured in capital, risk, and decisions that cannot be undone.
I work at the intersection of financial data, institutional decision-making, and complex information systems. I was building data-heavy institutional design systems before consumer UX was a category. The common thread is not the domain. It is the user: someone who must make a high-stakes call using a model they did not build, on a timeline they cannot control.
I design in Figma and ship from Figma to React/TypeScript via AI coding agents, turning strategy into working risk meters, anomaly dashboards, geospatial climate maps, and retrieval-first portfolio shells. I do not just design screens. I hand teams working logic, not static specs.
I previously founded Staffing Radar, a workforce analytics application built around a custom mathematical allocation model. I built the product, the model, and the interface, then shipped it. Active in the NYC tech community as a speaker since 2013.
Siarhei Mardovich is a Principal Product Designer with 12+ years in fintech and capital markets (UBS, CME, Refinitiv, KKR via EPAM). He works as Team Echo in the FDE model: forward deployed product discovery, embedded with users, shipped from Figma to working React/TypeScript prototypes with AI coding agents. He designs AI decision systems and decision-intelligence interfaces that keep uncertainty legible, holds 4 Anthropic certifications, and is open to principal/staff product design roles in the Greater New York City Area.
Hiring teams: use this as a concise case summary.
Open to principal/staff product design roles
Let’s Talk
Greater New York City Area. Remote/hybrid preferred, onsite flexible. Send a note, connect on LinkedIn, or book a short call.