Гринишин

Daniil Hrynyshyn
DATA SCIENTIST | RISK ASSESSMENT, FRAUD DETECTION & PRODUCTION ML
Riga, Latvia | [відкрити контакти](див. вище в блоці «контактна інформація») | [відкрити контакти](див. вище в блоці «контактна інформація»)

PROFESSIONAL SUMMARY

Data Scientist and Machine Learning Engineer with 4+ years of combined experience in applied ML, software
engineering, technical research and project coordination. Delivered 3 production machine learning models: 2 for credit
scoring and 1 for a hospital. Experienced in risk assessment and fraud detection, end-to-end Python/SQL data
pipelines, model evaluation, and integrating ML inference with APIs and CRM workflows. Strong AWS and Kubernetes
background with cross-functional collaboration across business, engineering and healthcare teams.

TECHNICAL SKILLS

Machine learning & data science: Python, SQL, scikit-learn, PyTorch, XGBoost, pandas, NumPy; supervised and
unsupervised learning, classification, regression, gradient boosting, clustering, deep learning, RNN/LSTM, NLP/LLM
applications.
Risk assessment & fraud detection: Credit scoring, default prediction, fraud screening, AWS-based facial verification,
phone-number and geolocation checks, risk segmentation, imbalanced classification.
Statistics & model evaluation: Statistics, probability, linear algebra, feature engineering, ROC-AUC, PR-AUC,
precision/recall, calibration, out-of-time validation, experiment design, drift and performance monitoring.
Production ML & cloud: Model deployment, REST APIs, FastAPI, MLflow, Docker, Kubernetes, AWS/EKS, Azure, Redis,
PostgreSQL, GitHub Actions, CI/CD, automated testing; Java (university projects).
Research & delivery: Time-series forecasting, pretrained models (Amazon Chronos), reproducible experiments, Agile
collaboration, part-time project management, scientific manuscripts in preparation.

PROFESSIONAL EXPERIENCE

Machine Learning Engineer - Credit Risk & Fraud Detection
Consumer-lending company (confidential) | Sep 2023 - Aug 2025
• Designed, trained, evaluated and deployed 2 production ML models for credit scoring and risk assessment using Python,
SQL, scikit-learn, XGBoost and logistic regression.
• Integrated model predictions into backend APIs and CRM decision workflows, working with developers, data engineers
and business stakeholders on automated risk decisions.
• Implemented fraud-screening processes combining AWS-based face matching, phone-number and geolocation signals
to identify suspicious applications.
• Defined ML evaluation frameworks with ROC-AUC, PR-AUC, precision/recall, out-of-time testing, calibration, segment
analysis and business-aware decision thresholds.
• Sourced and preprocessed structured data, engineered features, investigated missing values and monitored model
quality and risk segments.

DevOps / SRE Engineer - Applied AI Platform
Accenture | Sep 2025 - Present
• Support production AI platform services on AWS/EKS and Kubernetes with Docker, Redis, PostgreSQL and cloud
infrastructure, focusing on availability and scalability.
• Build Python automation, environment diagnostics, CI/CD validation and service health checks; troubleshoot APIs,
dependencies and production platform issues.
• Collaborate with developers, infrastructure engineers and stakeholders to improve reliable deployment, monitoring and
release practices.

Backend Developer Intern
Accenture | Feb 2025 - Aug 2025
• Developed backend and REST API integrations, automated data-processing workflows and PostgreSQL-backed services
in an Agile engineering environment.

Daniil Hrynyshyn | Data Scientist

PROFESSIONAL EXPERIENCE (CONTINUED)

Research Engineer - Healthcare Machine Learning (Part-time)
Pauls Stradiņš Clinical University Hospital | Aug 2025 - Present
• Delivered 1 production machine learning model for a hospital workflow, contributing to data preparation, model
development, validation and integration with the healthcare team.
• Worked with glucose-monitoring, nutrition, activity and patient time-series data, addressing irregular timestamps,
missing sensor values and data leakage.
• Compared statistical, tree-based and LSTM sequence models using participant-aware splits, forward-looking evaluation
and forecast-horizon analysis.

Research Engineer & Part-time Project Coordinator
Riga Technical University | Dec 2025 - Present
• Conduct applied ML research covering supervised learning, unsupervised clustering, deep learning, PyTorch, RNN/LSTM
and pretrained forecasting models such as Amazon Chronos.
• Coordinate project tasks, experiment planning, research documentation and communication across technical
stakeholders as part of part-time project management.
• Contribute to multiple scientific manuscripts in preparation; document methods, analyze results and maintain
reproducible experiments.

Part-time Project Lead & Backend Developer
Benefice Dance School Management Platform | 2024 - 2025
• Coordinated development with business stakeholders and led backend delivery of a management platform, including
role-based access, attendance and payments, using FastAPI, PostgreSQL and Docker.

IT Researcher
AB Park, Riga | Jun 2022 - Sep 2022
• Contributed to IT research and technical analysis in an early professional technology role.

EDUCATION

M.Sc. in Computer Systems - Artificial Intelligence | Riga Technical University | 2026 - Expected 2028
B.Sc. in Computer Systems | Riga Technical University | 2022 - 2025

LANGUAGES

English: C1 (fluent) | Ukrainian: Native | Russian: Fluent | Latvian: A2