Experience and responsibility
Vladimir Lovtsov
Engineering and product portfolio leader
I lead the work from a business challenge to a working product: the team, architecture, priorities, release, and continued development.
Target roles: CTO, CDO, and technology transformation leadership, with responsibility for strategy, teams, data, and business outcomes.
vladimir@lovtsov.devTelegram ↗LinkedIn ↗
Moscow · office, hybrid, or remote · English B2
Product launch
5 monthsfrom development start to production launch
December 2024 → April 2025Delivery speed
14 daysaverage time to market for product changes
Across the live production systemBusiness outcome
+30%increase in the share of credit offers resulting in a completed banking product
After redesigning the offer calculation and formation strategyThese are team results. My contribution is engineering leadership, architectural and product decisions, coordination, and accountability for delivery.Context and case studies →
Where I worked and what I owned
Innotech · T1 Group
Director of Project Portfolio Management · Development Cluster IT Lead
Personalized lending offers · client: VTB Bank
- Since December 2025, I have led a product portfolio with an estimated business impact of several billion RUB and a development cluster of several full-cycle cross-functional teams, owning priorities, resources, budgets, timelines, and dependencies.
- I turn business needs into product strategy, roadmaps, product and technical backlogs, and architecture; average time to market for product changes is 14 days.
- I oversee the real-time and batch platforms for personalized banking offers, processing tens of TB of data per day.
- I redesigned the credit-offer calculation and formation strategy; the share of offers resulting in a completed banking product increased by 30%.
- I took over the new Decision Engine project, a SAS RTDM-class product, as IT Lead in late September 2024; formed the team by November and started development in December.
- I launched the Decision Engine into production in April 2025, five months after development started.
- I established the full engineering lifecycle: discovery and requirements, architecture, development, testing, CI/CD, release management, and operations.
- I reorganized Big Data application services, brought the teams together, increased process automation from 40% to 80%, and nearly halved technical debt.
- As a Data Analyst, I helped turn a graph-platform project into the Mirion product by prototyping ETL and ML/AI solutions, researching graph algorithms, and shaping the product architecture.
How my responsibilities grew
- Director of Project Portfolio Management · Development Cluster IT Lead
- Decision Engine Project Director
- Decision Engine IT Lead
- IT Lead, Big Data Application Services
- Analytics Team Lead
- Data Analyst
Practices and technologiesPortfolio Management · Product & Backlog · Budgeting · Stakeholder Management · High-Load Systems · Event-Driven Architecture · Big Data · Apache Flink · Java · Scala · Python · CI/CD
T1 Group · Tech Guilds initiative
Project Lead · alongside core role
Organization design, engineering community, and expertise at scale
- I initiated the community and recruited more than 20 senior experts for targeted assistance; other community members also helped teams solve problems.
- By my estimate, community members resolved more than 1,000 engineering cases over the initiative’s lifetime and helped teams reuse proven solutions.
- I secured executive sponsorship and established a model for sharing engineering standards across the group.
- I curated the Data Engineering course in 2024, relaunched the Systems Analysis course in 2023 and developed its teaching materials; I also organised regular internal meetups.
Practices and technologiesOrg Design · Talent Network · Engineering Culture · Knowledge Management · IT Transformation
VTB Bank
Lead Data Analyst · Full-Stack Analyst
Enterprise data platform
- I designed solution architecture, data flows, and integrations over REST, gRPC, and Kafka.
- I developed PySpark ETL prototypes for Cloudera Hadoop data marts, including filtering and data-quality controls.
- I owned functional and non-functional requirements for antifraud, ML/AI, and risk models and led data-quality reviews of vendor solutions.
Practices and technologiesPySpark · Hadoop · Kafka · Python · SQL · ArangoDB · REST · gRPC
Kerama Marazzi
Senior Data Quality Analyst
Mohawk Industries · Data Governance and master data
- I designed the enterprise data architecture and secured executive approval for an adapted Data Governance model.
- I led the redesign of data flows, removed the causes of errors in daily reporting to US investors, and scaled the solution across the Russian group.
- I established systematic data-quality controls and reduced operational risk across the enterprise application landscape.
Practices and technologiesData Governance · MDM · Data Quality · Python · SQL · 1C
Nestlé Russia
Data Back Office Manager · Financial Analyst
Finance, master data, and process automation
- I led a small team and reduced request-processing SLA from two months to five business days.
- I developed financial models for marketing activities and investment decisions.
- I contributed to a digital-merchandising model and an algorithm for deduplicating retail outlets.
Practices and technologiesProcess Optimization · SQL · Python · ETL · MS SQL · Dynamics CRM · SAP
What I bring to the work
Portfolio and product
- Portfolio, program, and project management
- Product strategy, roadmap, and backlog
- Prioritization by value, risk, and effort
- Working knowledge of PMBOK principles for scope, schedule, budget, resource, and risk management
Delivery and quality
- Hands-on Scrum and Kanban; working knowledge of SAFe principles
- End-to-end SDLC and quality gates
- CI/CD, release management, and operations
- Time to market, reliability, and technical debt
People and collaboration
- Stakeholder management and negotiation
- Risks, dependencies, change, and escalation management
- Resource planning and feedback
- Organization design, hiring, and professional development
Architecture, data, and AI
- High-load and microservice systems
- Big Data, stream processing, and Data Governance
- Event-driven architecture and integrations
- AI tools in the engineering workflow
My own engineering practice
Creator · personal product
LAF · engineering management with AI agents ↗
Coordinates an autonomous delivery queue with decomposition, isolated workspaces, checks, retained context, and budget controls.
I use it in my own projects and am considering commercializing it.Creator · planning assistant for engineering leaders
Planograph AI ↗
Connects the backlog, dependencies, specialist capacity, and annual planning. Helps compare delivery scenarios against team constraints.
Uses an OR-Tools CP-SAT allocation model; a personal product, not a corporate deployment.Creator of personal implementations
AI / ML · RAG ↗
Text extraction, request analysis, forecasting, and knowledge retrieval. The RAG assistant combines lexical and semantic search with API / MCP access.
Working implementations and research scenarios; adaptation depends on the specific use case.Education and development
Bauman Moscow State Technical University
- Management, BSc · September 2014 — February 2017 · Faculty of Engineering Business and Management
- Nanoengineering in electronics, BSc · September 2012 — June 2016
I began my second degree in the third year of my first, studying both programmes concurrently from September 2014.
Further training
- Hi-PO: IT team management · Stratoplan / T1 · 2022
- Spark for Data Engineering · Big Data School · 2021
- Data Science · Yandex Practicum · 2020
Speaking and sharing experience
- Saint HighLoad++
- Analysis and Management in IT
Accelerating development with AI
- Analyst Days
Behold the path of data, Padawan
- Analyst Days
Don’t paint the grass: data risk and value