Ilya Daronin

[email protected] • +6281246592350

PROFESSIONAL SUMMARY

Results-driven Data Scientist and Machine Learning Engineer with 1–2 years of experience delivering scalable, data-driven solutions that enhance business performance. Proficient in Python, SQL, TensorFlow, PyTorch, and MLOps practices, with proven success in building end-to-end ML pipelines that improved model accuracy by 15% and reduced processing time by 20%. Skilled in predictive modeling, cloud computing (AWS/GCP), and big data analytics, adept at translating complex data insights into actionable strategies that drive informed decision-making and operational efficiency.

WORK EXPERIENCE

Machine Learning Engineer with Data Science skills
11/2023 - 11/2025
Tech Solutions Group
• Developed and deployed an end-to-end ML pipeline (Python, Scikit-learn, Docker), improving model accuracy by 15% and reducing processing time by 20%.
• Optimized feature engineering and automated data quality checks, reducing data-related errors by 30%.
• Built and deployed a prediction API (FastAPI, Docker) achieving 99% uptime and response time under 100 ms.
• Created a customer risk prediction model that helped reduce operational costs by 12%.
• Implemented MLflow for experiment tracking, improving reproducibility and accelerating experimentation by 40%.
• Integrated large language model components (OpenAI embeddings), tripling text processing speed and enabling faster insights extraction
• Automated ETL workflows using Airflow/Python, cutting manual analyst work by 25%.

EDUCATION

Bachelor's degree, Energy Management and Systems Technology
09/2014 - 06/2019
Belarusian National Technical University

SKILLS

Technical Skills: Python, NumPy, Pandas, Scikit-learn, SQL, Feature Engineering, EDA, Supervised & Unsupervised Learning, Model Optimization, NLP, LLMs, Time Series, TensorFlow, PyTorch, ETL, ML Pipelines, REST APIs, Model Deployment
Soft Skills: Problem Solving, Cross-Functional Collaboration, Clear Technical Communication, Documentation, Task Ownership, Critical Thinking, Iterative Deliver, Adaptability
Tools: Git, GitHub, GitLab, Docker, Docker Compose, MLflow, Weights & Biases, Apache Spark, CI/CD Fundamentals, AWS (S3, EC2, Lambda, SageMaker), GCP (Cloud Storage, Vertex AI, Compute Engine)
Other: Prompt Engineering, LLM Integration, Applied Data Science Domain Knowledge, Basic DevOps Practices

CERTIFICATIONS

IBM Data Science Professional Certificate
IBM
Machine Learning
Stanford University

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