Maksym

Maksym Katkalov
Business Analyst
[open contact info](look above in the "contact info" section) [open contact info](look above in the "contact info" section)

Lviv/Remote num_kat9

WhatsApp 22.02.2002

PROFILE

Data-driven Business & Systems Analyst with extensive experience in process modeling, data analytics, and end-
to-end SDLC/AI product delivery across enterprise FinTech and mobile subscription environments. Holds a
Bachelor’s Degree in Law, combining rigorous analytical thinking with high precision in requirement elicitation,
process architecture, and drafting technical specifications (BRD, SRS, User Stories, Acceptance Criteria).
Proficient in bridging business stakeholders, data science units, and engineering teams by translating complex
operational challenges and unit economics into functional roadmaps, data models, and actionable backlog items.
Experienced in market intelligence, subscription metrics (LTV, Retention, ARPU, Churn), Root Cause Analysis
(RCA), and process optimization. Possesses a strong technical toolkit spanning Python, SQL (PostgreSQL,
BigQuery), REST APIs, Power BI, Grafana, and the ELK stack.
Adept at leading initiatives throughout the full delivery lifecycle — from process architecture design (0-to-1) and
stakeholder alignment to automated pipeline implementation, UAT, and executive dashboarding. Strong cross-
functional communicator focused on eliminating operational inefficiencies, improving service reliability, and
driving data-informed business growth.

PROFESSIONAL EXPERIENCE

08/2021 – 04/2024 HOSTiQ
Data Analyst / Systems Analyst
Worked as a Market Data Analyst specializing in subscription apps and mobile unit
economics, evaluating competitive intelligence and identifying high-growth niches
across US and Tier-1 iOS markets. Conducted comprehensive teardowns of competitor
paywalls, web2app onboarding flows, and monetization models, reconstructing key
subscription performance indicators such as trial-to-paid conversion, LTV, ARPU, churn,
MRR, and retention profiles. Cross-verified store performance data (AppMagic, Sensor
Tower, SimilarWeb) and analyzed ad intelligence across Meta, Google, and TikTok to
evaluate competitor UA strategies and give CPO-level go/no-go product
recommendations. Built automated data pipelines and interactive BI dashboards using
Python (Django, SQLAlchemy, Alembic, PyTest, Pydantic), SQL, PostgreSQL, BigQuery,
and Power BI to extract, clean, and visualize complex metrics. Leveraged Redis,
MongoDB, REST APIs, and Google Sheets for web scraping, ad attribution mapping, and
market trend tracking to optimize user acquisition frameworks and drive data-informed
business decisions.

04/2024 – Present Raiffeisen Bank
Incident Analyst & AI Delivery Manager
Analyzed and optimized enterprise incident management processes across critical
banking infrastructure, taking full ownership of post-incident reports, SLA/SLO metrics,
and executive business communications. Built and owned the organization’s Problem
Management framework entirely from scratch, establishing structured Root Cause
Analysis (RCA) protocols and driving cross-functional follow-ups and action items with
technical teams to eliminate recurring failures. Served as the end-to-end AI Delivery
Manager for dedicated engineering teams, leading the end-to-end delivery lifecycle of
internal AI products, fine-tuned LLM models, and predictive monitoring tools. Managed
the AI project backlog, defined product roadmaps, and bridged business needs with data
science capabilities by designing prompt engineering workflows, assessing model
performance metrics, and validating solution ROI. Built interactive dashboards,
operational reports, and availability insights using Power BI, SQL, Grafana, and the ELK
stack to track SLA adherence and drive leadership decisions. Facilitated cross-functional
alignment between C-level stakeholders, Product Owners, Data Scientists, and SRE/Dev
units, while documenting AI release pipelines, post-mortems, and process guidelines in
Jira and Confluence to ensure scalable and compliant enterprise AI adoption.

PROJECTS

Banking Incident Management
Reworked our operational response and follow-up flow for critical outages in the banking infrastructure. I focused
on building clear communication loops between business users, SRE, and dev teams during major issues, making
sure no post-incident action item got lost. I also designed custom tracking dashboards using SQL, Power BI,
Grafana, and ELK to monitor MTTR, service uptime, and overall SLA adherence for leadership.

Building the Problem Management Process from Scratch
Designed and authored the bank's complete Problem Management framework from the ground up to eliminate
systemic incident root causes and recurring risks. I defined the entire process architecture—from high-level
workflows and role interaction schemes (L1, Problem Coordinator, Problem Manager, Technical Teams) to core
artifacts like Known Error records, RCA evidence standards, and action item tracking. I introduced both reactive
triggers (post-mortem follow-ups) and proactive mechanisms (monitoring trends, SLO/SLI degradation, and AI-
discovered candidates) to build an auditable engineering backlog. This shifted our operational mindset from
temporary incident workarounds to structural defect elimination and evidence-backed closure governance.

Enterprise AI Delivery & Tooling Adoption
Managed the rollout of internal AI tools, custom MCP servers, and automation helpers for engineering and support
teams. To drive actual usage, I shifted our licensing approach from passive seat allocation to real activity tracking,
which boosted active daily usage from 30% to 62%. I also coordinated team onboarding, prompt templates, and
workflow integrations (like automated YAML configs and AI code reviews), saving engineers around 3–4 hours a
week per person.

SKILLS

BRD, SRS, User Stories, Problem Management (0-to-1), Subscription Analytics (LTV,
Acceptance Criteria, BPMN Root Cause Analysis (RCA), ITIL Retention, ARPU, Churn, MRR),
Process Mapping, SDLC, UAT, Practices, SLA/SLO Web2App & Onboarding Funnel
Technical Writing (Confluence). Optimization, Escalation Teardowns, Unit Economics.
Frameworks.
PostgreSQL, BigQuery, SQLite, Power BI, Tableau, Grafana, ELK
Complex Queries, Database Exploratory Data Analysis (EDA), Stack, Executive Interactive
Schema Design, Relational Data Statistics, Machine Learning Dashboards, Advanced Google
Modeling, Query Optimization. Fundamentals, Pandas, NumPy, Sheets.
Matplotlib, Seaborn.
Python 3, FastAPI, Django, Redis, MongoDB, Django ORM,
Django REST Framework, Scrapy, BeautifulSoup, ETL NoSQL/Key-Value Stores, Data
SQLAlchemy, Alembic, Pydantic, Automation, Automated Data Persistence Strategies.
PyTest, OOP, Design Patterns. Extraction Pipelines, Payload
Mapping & Validation. Scrum, Kanban, Waterfall, Jira,
AI Delivery Management, Fine- Troubleshooting & Issue
tuned LLMs, Custom MCP Linux CLI, Docker, Docker Elimination, Upper-Intermediate
Servers, Prompt Engineering Compose, AWS (EC2, Redshift), English.
Workflows, AI FinOps & CI/CD Pipelines, Git, GitHub,
Adoption Metrics. REST & SOAP APIs.

EDUCATION

2019 – 2023 Bachelor's degree in law
Kharkiv, Ukraine Yaroslav Mudryi National Law University

INTERESTING FACT

I never dreamed of becoming an astronaut or a pilot, but I did dream of becoming a hacker.