We are seeking an experienced Senior/Middle Data Scientist with a passion for Large Language Models (LLMs) and cutting-edge AI research. In this role, you will focus on designing and prototyping data preparation pipelines, collaborate closely with data engineers to transform your prototypes into scalable production pipelines, and actively develop model training pipelines with other talented data scientists. Your work will directly shape the quality and capabilities of our models by ensuring we feed them the highest-quality, most relevant data possible. The datasets you build directly determine model capability, safety, and cost — raising downstream task accuracy, reducing training waste, and accelerating time-to-market for product teams.

About Us

Kyivstar.Tech is a Ukrainian hybrid IT company and a resident of Diia.City.

We are a subsidiary of Kyivstar, one of Ukraine's largest telecom operators.

Our mission is to change lives in Ukraine and around the world by creating technological solutions and products that unleash the potential of businesses and meet users' needs.

Over 500+ KS.Tech specialists work daily in various areas: mobile and web solutions, as well as design, development, support, and technical maintenance of high-performance systems and services.

We believe in innovations that truly bring quality changes and constantly challenge conventional approaches and solutions. Each of us is an adherent of entrepreneurial culture, which allows us never to stop, to evolve, and to create something new.

Responsibilities

Design, prototype, and validate data preparation and transformation steps for LLM training datasets, including cleaning and normalization of text, filtering of toxic content, deduplication, denoising, detection, and deletion of personal data
Form specific SFT/RLHF datasets from existing data, including data augmentation/labeling with LLM as teacher
Analyze large-scale raw text, code, and multimodal data sources for quality, coverage, and relevance
Develop heuristics, filtering rules, and cleaning techniques to maximize training data effectiveness
Collaborate with data engineers to hand over prototypes for automation and scaling
Research and develop best practices and novel techniques in LLM training pipelines
Monitor and evaluate data quality impact on model performance through experiments and benchmarks
Research and implement best practices in large-scale dataset creation for AI/ML models
Document methodologies and share insights with internal teams

Required Qualifications

Education & Experience:

3+ years of experience in Data Science or Machine Learning, preferably with a focus on NLP
Proven experience in data preprocessing, cleaning, and feature engineering for large-scale datasets of unstructured data (text, code, documents, etc.)
Advanced degree (Master’s or PhD) in Computer Science, Computational Linguistics, Machine Learning or a related field is highly preferred

NLP Expertise

Good knowledge of natural language processing techniques and algorithms
Hands-on experience with modern NLP approaches including embedding models, semantic search, text classification, sequence tagging (NER), transformers/LLMs, RAGs
Familiarity with LLM training and fine-tuning techniques, and data requirements

ML & Programming Skills

Proficiency in Python and common data science and NLP libraries (pandas, NumPy, scikit-learn, spaCy, NLTK, langdetect, fasttext)
Strong experience with deep learning frameworks such as PyTorch or TensorFlow for building NLP models.
Ability to write efficient, clean code and debug complex model issues

Data & Analytics

Solid understanding of data analytics and statistics
Experience in experimental design, A/B testing, and statistical hypothesis testing to evaluate model performance
Comfortable working with large datasets, writing complex SQL queries, and using data visualization to inform decisions

Deployment & Tools

Experience deploying machine learning models in production (e.g., using REST APIs or batch pipelines) and integrating with real-world applications
Familiarity with MLOps concepts and tools (version control for models/data, CI/CD for ML)
Experience with cloud platforms (AWS, GCP or Azure) and big data technologies (Spark, Hadoop, Ray, Dask) for scaling data processing or model training is a plus

Communication & Personality

Experience working in a collaborative, cross-functional environment
Strong communication skills to convey complex ML results to non-technical stakeholders and to document methodologies clearly
Ability to rapidly prototype and iterate on ideas

What We Offer

Office or remote – it’s up to you. You can work from anywhere, and we will arrange your workplace
Remote onboarding
Performance bonuses for everyone (annual or quarterly — depends on the role)
We train employees: with the opportunity to learn through the company’s library, internal resources, and programs from partners
Health and life insurance
Wellbeing program and corporate psychologist
Reimbursement of expenses for Kyivstar mobile communication