Jobs

Шукаємо Data Scientist, що працюватиме з R&D, регресіями та табличними даними, zero-to-one продуктом на глобальному ринку. Вплив на алгоритми та бізнес, експерименти без обмежень. Топові умови, повний ремоут. 

Main Responsibilities:

– Be responsible for DS-ML-related solutions developed by all Service and Delivery(SnD) squads: maintenance and improvement of existing solutions; design, development, and implementation of new solutions

– Provide technical leadership for other SnD DSs

– Test developed algorithms, work with the SnD team within UAT, adapt, and reach DOD and DOR

– Verify key tasks done by SnD DS, such as model training and AB test design

– Conduct code reviews for DS-ML-related solutions

– Automate DS work in SnD.Develop data requirements for SnD implementation projects

– Cooperate with IM and DE to achieve and maintain the optimal dataset configuration according to DS-ML needs

– Measure solution stability, quality, and effectiveness; transparently communicate the current state of things to other roles/teams, and suggest and implement improvements

– Regularly collaborate (provide prototypes/ideas/detailed feature requests) with RnD Teams on tools for SnD

Mandatory Requirements:

– A minimum of 3 years of experience in data science or a related field

– Proficiency in SQL for data manipulation and extraction

– Strong Python skills, capable of writing modular and readable code for experiments and prototypes

– A solid mathematical background, preferably in a Computer Science-related field

– Proficiency in the scientific Python toolkit, including NumPy, pandas, scikit-learn, and either Keras/TensorFlow or PyTorch

– Familiarity with Time Series Forecasting approaches

– Experience in statistical testing methodologies, including A/B testing

– At least 3 years of experience working with tabular and mixed (multimodal) data (e.g., tabular data combined with text, audio, or images).

– Upper-intermediate or higher level of English (for future communication with clients and user interviews)

Soft skills

– Analytical mindset and strong critical thinking abilities

– Leadership skills to efficiently organize the data team (Data Scientists, Data Engineers, Data Analysts)

– Agile approach, with the ability to experiment and test hypotheses in an unstable business environment

– Business-oriented mindset, able to translate complex models into simple business language

– Excellent presentation skills, capable of communicating complex ideas effectively

– Curiosity and a commitment to continuous learning within the domain

– Strong team player, able to collaborate effectively with cross-functional teams

We offer:

– Rich innovative software stack, freedom to choose the best suitable technologies

– Remote-first ideology: freedom to operate from the home office or any suitable coworking

– Flexible working hours (we start from 8 to 11 am) and no time tracking systems on

– Regular performance and compensation reviews

– Recurrent 1-1s and measurable OKRs

– In-depth onboarding with a clear success track

– Competera covers 70% of your training/course fee

– 20 vacation days, 15 days off, and up to one week of paid Christmas holidays

– 20 business days of sick leave

– Partial medical insurance coverage

– We reimburse the cost of coworking

This is a mixed role that require someone who loves Data and Business analysis, has good python skills in data processing and analysis.

Requirements:

- Analyze and Process Data (data cleaning, data processing, creating data pipelines)

- Actively participate in Business Analysis (analysis of user needs)

- Experience with Python scripting

- Some Data Science knowledge is preferable

- Curious, fast-learning, organized, responsible

Responsibilities:

- Design and develop data processing scripts

- Monitor and troubleshoot data processing pipelines 

- Analyze and understand user needs, come up with ideas on how to create better data/content for our users

- Design, develop, and refine prompts to optimize the responses from Large Language Models

- Create recommendation systems, integrate RAG for content generation

We Offer:

- WFH and flexible working hours 

About you:

We are hiring an experienced Machine Learning Engineer to join our team. This specialist will be responsible for refactoring our ML codebase, integrating new infrastructure, and developing reusable modules. Working closely with our data science and engineering teams, the Machine Learning Engineer will play a key role in enhancing the maintainability, scalability, and performance of our ML systems.

About project:

Join our client’s innovative team, working at the forefront of agricultural technology. They are dedicated to developing cutting-edge solutions that combine IoT and AI to optimize processes in smart agriculture. The core objective of this project is to monitor and improve crucial natural processes, thereby enhancing efficiency and sustainability in the agricultural sector.

Our client’s ML infrastructure processes data from IoT sensors placed in beehives to monitor temperature, humidity, and other environmental factors. This data is used to create predictive models focused on colony health, queen problems, and pollination efficiency. By leveraging real-time data and advanced technologies, the platform helps to drive better outcomes for food production and biodiversity, making a tangible impact on global food systems. The team is looking for someone who can help improve the underlying architecture of these systems while maintaining their functionality and accuracy.

Your area of responsibility:

• Restructuring and optimizing existing Machine Learning code to enhance its readability, ease of maintenance, and performance, all while ensuring core functionality is preserved.
• Integrating ML models and their associated pipelines with recently developed infrastructure elements to guarantee smooth operation and compatibility.
• Designing and implementing reusable Machine Learning modules intended for common tasks such as preparing data, engineering features, and training or evaluating models.
• Developing and deploying both unit and integration tests to uphold code quality standards and confirm reliability.
• Identifying and putting into practice improvements aimed at boosting model performance, increasing efficiency, and supporting scalability.
• Collaborating effectively with colleagues who are not located in the same place, offering guidance and participating in code review processes to receive feedback.

Skills and requirements:

• A minimum of 5 years’ professional experience in software engineering, with a strong focus on Machine Learning systems.
• Demonstrated high proficiency in Python and essential ML libraries (such as TensorFlow, PyTorch, and scikit-learn).
• A proven history of successfully refactoring complex existing codebases without compromising original functionality.
• Experience in the design and deployment of software components and libraries intended for reuse.
• Familiarity with standard ML pipelines, including processes for handling and deploying data.
• Knowledge of fundamental software engineering practices, such as managing versions, testing code, and creating documentation.
• Experience working with systems that are distributed and software stacks that are cloud-based.
• Strong capabilities in solving problems, with a focus on creating solutions that are practical and easy to maintain over time.

Will be a plus:

• Practical experience with MLOps tools and common practices in that field.
• Understanding and experience with technologies used for containerization and orchestration (like Docker or Airflow).
• Familiarity with continuous integration/continuous deployment (CI/CD) pipelines specifically for ML systems.
• Experience using tools designed for data versioning.
• Exposure to frameworks used for processing data on a large scale.
• Experience working effectively with teams that are geographically dispersed and in roles such as consulting or contract work.

We offer:

- Висококласні робочі умови: спільнота першокласних інженерів, близько 90% нашої команди це Middle та Senior; цікаві та довгострокові проєкти у різних сферах; можливість змінити проєкт в разі необхідності;

- Конкурентна ринкова компенсація в валюті (не в гривневому еквіваленті), яка виплачується без затримок;

- Власний план розвитку та регулярні перегляди компенсації;

- Оплачувані відпустки (20 днів) та лікарняні дні (5 днів);

- Всі державні свята за Українським законодавством є вихідними;

- Можливість працювати з будь-якою точки світу — ми знайдемо юридичний варіант, допоможемо легалізуватися або проконсультуємо з цього питання.

- Бухгалтерський супровід;

- Юридична підтримка в межах України;

- Повноцінна HR-підтримка та турбота.

We are seeking a highly skilled and versatile Data Specialist who combines deep expertise in statistics and machine learning, strong software engineering and data infrastructure skills, and a genuine interest in the automotive industry.

You will be instrumental in designing and implementing predictive models for vehicle pricing, building scalable data pipelines, and contributing to the architecture and development of our next-generation Automotive Data Warehouse.

Requirements:

- Advanced knowledge in statistics, machine learning, and predictive modeling (e.g., regression, time-series forecasting, ensemble models);

- Strong software development background in Python or C#;

- Excellent command of SQL and experience with relational and analytical databases;

- Solid understanding of Data Warehousing concepts and ETL/ELT pipeline design;

- Familiarity with cloud services like AWS or Azure (basic knowledge required);

- Practical experience with data cleaning, data transformation, and data quality management;

- Experience working with modern data platforms (e.g., ClickHouse, Redshift, Snowflake, or equivalent);

- Proven ability to build and maintain production-grade analytical systems;

- Strong interest or background in automotive data, car technologies, or the vehicle marketplace.

Will be a plus:

- Experience in building real-time or batch forecasting tools for market analytics;

- Prior work with automotive datasets, including pricing, maintenance, user preferences, or telematics;

- Knowledge of media data processing (images, video, 3D) or user interaction analysis.

Responsibilities:

- Design and develop mathematical models for car pricing, including historical, market, and user-influenced factors;

- Build and optimize end-to-end data pipelines: ingestion, cleaning, transformation, aggregation, and storage;

- Work with large and heterogeneous datasets, including structured data (prices, vehicle history), unstructured data (media), and user behavior analytics;

- Apply classical statistical methods and modern ML/AI techniques to forecast trends and derive actionable insights;

- Collaborate on the technical implementation of the dR Data Warehouse, including integration of internal and external data sources;

- Ensure performance, scalability, and economic efficiency in all data systems and models.

We offer:

- Variety of domains;

- Full stack of technologies;

- Professional and highly interactive team environment;

- Management style based on openness and trust;

- Stable support in personal education and growth;

- Worthy compensation;

- Active community with regular knowledge sharing;

- Flexible work conditions.

Our client is a leading SaaS company offering pricing optimization solutions for e-commerce businesses. Its advanced technology utilizes big data, machine learning, and AI to assist customers in optimizing their pricing strategies and maximizing their profits.

About the Role:
As a Data Scientist you’ll play a critical role in shaping and enhancing our AI-driven pricing platform.

Key Responsibilities:

• Develop and Optimize Advanced ML Models: Build, improve, and deploy machine learning and statistical models for forecasting demand, analyzing price elasticities, and recommending optimal pricing strategies.
• Lead End-to-End Data Science Projects: Own your projects fully, from conceptualization and experimentation through production deployment, monitoring, and iterative improvement.
• Innovate with Generative and Predictive AI Solutions: Leverage state-of-the-art generative and predictive modeling techniques to automate complex pricing scenarios and adapt to rapidly changing market dynamics.

Required Competence and Skills:

• A Master’s or PhD in Computer Science, Physics, Applied Mathematics or a related field, demonstrating a strong foundation in analytical thinking.
• At least 5 years of professional experience in end-to-end machine learning lifecycle (design, development, deployment, and monitoring).
• At least 5 years of professional experience with Python development, including OOP, writing production-grade code, testing, and optimization.
• At least 5 years of experience with data mining, statistical analysis, and effective data visualization techniques.
• Deep familiarity with modern ML/DL methods and frameworks (e.g., PyTorch, XGBoost, scikit-learn, statsmodels).
• Strong analytical skills combined with practical experience interpreting model outputs to drive business decisions.

Nice-to-Haves:

• Practical knowledge of SQL and experience with large-scale data systems like Hadoop or Spark.
• Familiarity with MLOps tools and practices (CI/CD, model monitoring, data version control).
• Experience in reinforcement learning and Monte-Carlo methods.
• A solid grasp of microeconomic principles, including supply and demand dynamics, price elasticity, as well as econometrics.
• Experience with cloud services and platforms, preferably AWS.

Why Us?

We provide 20 days of vacation leave per calendar year (plus official national holidays of a country you are based in).

We provide full accounting and legal support in all countries we operate.

We utilize a fully remote work model with a powerful workstation and co-working space in case you need it.

We offer a highly competitive package with yearly performance and compensation reviews.

Strong background in data science from retail or logistics. 

Must-Have Skills
• Proficient in Python, including libraries such as:
• pandas, numpy, scikit-learn
• FastAPI, SQLAlchemy

Nice to Have
• Experience with agent frameworks (e.g., LangChain, Haystack, Prompt Flow)
• Hands-on experience with, or strong interest in learning, deployment and orchestration of agent-based systems
• Familiarity with Vector Databases (e.g., Qdrant)
• Experience with Graph Databases (e.g., Neo4j)
• Knowledge of Streamlit for building data apps

As a Senior Data Scientist, you will play a pivotal role in enhancing PDF Expert’s data-driven capabilities by developing predictive models and actionable insights. You will be responsible for designing and implementing data science solutions that improve product performance, user engagement, and business outcomes. You will work closely with product, marketing, and engineering teams to translate complex data into strategic decisions and ensure seamless integration of data insights into the product.

What will you do:

• Transform large data sets, analyze trends, and generate actionable insights to optimize product strategies, user acquisition, and design improvements.
• Build, test, and deploy statistical and predictive models to support product and marketing initiatives, including churn prediction and customer segmentation.
• Set up intelligent alert systems and dashboards to monitor key metrics and detect anomalies, ensuring proactive issue resolution.
• Conduct in-depth analysis to understand customer behavior, segment users based on value and usage, and develop targeted strategies for retention and conversion.
• Develop and maintain regular reports and visual dashboards, clearly communicating data-driven insights to support strategic decision-making.
• Partner with product, marketing, and engineering teams to integrate data insights into product development, marketing campaigns, and performance optimization.
• Build forecasting models to predict growth, revenue impact, and product adoption, contributing to data-driven planning and strategy.

About you:

• At least 5 years of experience as a Data Scientist working with products.
• Proficiency in Python for data analysis, modeling, and automation.
• Strong understanding of statistical methods and their application in data interpretation and model building.
• Hands-on experience building and deploying machine learning models, including churn prediction, LTV estimation, and clustering.
• Skilled in developing and maintaining data pipelines and integrating machine learning models into production.
• Experience working with at least one BI tool, such as Power BI or Tableau, for data visualization and reporting.
• Familiarity with big data technologies like Google Big Query, Snowflake, or Amazon Redshift.
• A collaborative mindset, comfortable working with product, marketing, and engineering teams.
• Ability to independently manage tasks and initiatives, driving projects to completion.

Would be a plus:

• Familiarity with marketing analytics and the ability to analyze campaign performance and customer segmentation.
• Experience with Google BigQuery for data processing and analysis.
• Expertise in designing, conducting, and interpreting A/B tests to inform product decisions.

FAVBET Tech develops software that is used by millions of players around the world for the international company FAVBET Entertainment.
We develop innovations in the field of gambling and betting through a complex multi-component platform which is capable to withstand enormous loads and provide a unique experience for players.

 

About the Role:

We are looking for a Data Scientist to join our growing team. In this role, you will work closely with the marketing, product, and engineering teams to deliver data-driven insights and build end-to-end machine learning solutions that support strategic decisions and product enhancements.

Responsibilities:

• Work on one of the following projects: User segmentation, Lifetime Value (LTV) prediction, Churn prediction.
• Collaborate with marketing and product teams to understand business needs and deliver data-driven solutions.
• Analyze large-scale datasets to uncover actionable insights that drive business and product outcomes.
• Build, validate, and deploy machine learning models to solve real-world problems.
• Partner with engineering teams to ensure access to reliable data sources and develop robust feature pipelines.
• Design and conduct A/B tests to measure the impact of new features and changes.
• Present analytical findings and model results clearly to business stakeholders.

Required Qualifications:

• Minimum of 2 years of experience as a Data Scientist or ML Engineer.
• Proficiency in Python, including libraries such as sklearn, lightgbm, keras/pytorch/jax.
• Proficiency in SQL, including writing complex queries.
• Hands-on experience designing, running, and interpreting A/B tests.
• Experience with version control systems such as GitHub, GitLab, or Bitbucket.

Nice to Have:

• Experience with cloud data platforms, ideally AWS.
• Familiarity with Docker or other containerization tools.
• Understanding of MLOps fundamentals and best practices.

We offer:

• 30 days off — we value rest and recreation.
• Medical insurance for employees and the possibility of training employees at the expense of the company and gym membership.
• Remote work or the opportunity — our own modern lofty office with spacious workplace, and brand-new work equipment (near Pochaina metro station).
• Flexible work schedule — we expect a full-time commitment but do not track your working hours.
• Flat hierarchy without micromanagement — our doors are open, and all teammates are approachable.

About project

Provectus helps companies adopt ML/AI to transform the ways they operate, compete, and drive value. The focus of the company is on building ML Infrastructure to drive end-to-end AI transformations, assisting businesses in adopting the right AI use cases, and scaling their AI initiatives organization-wide in such industries as Healthcare & Life Sciences, Retail & CPG, Media & Entertainment, Manufacturing, and Internet businesses.

We are seeking a highly skilled Machine Learning (ML) Tech Lead with a strong background in Large Language Models (LLMs) and AWS Cloud services. The ideal candidate will oversee the development and deployment of cutting-edge AI solutions while managing a team of 5-10 engineers. This leadership role demands hands-on technical expertise, strategic planning, and team management capabilities to deliver innovative products at scale.
 

Responsibilities:

• Leadership & Management
• Machine Learning & LLM Expertise
• AWS Cloud Expertise
• Technical Execution
• Team Development & Communication
   

Qualifications:

• Proven experience with LLMs and NLP frameworks (e.g., Hugging Face, OpenAI, or Anthropic models);
• Strong expertise in AWS Cloud Services;
• Strong experience in ML/AI, including at least 2 years in a leadership role;
• Hands-on experience with Python, TensorFlow/PyTorch, and model optimization;
• Familiarity with MLOps tools and best practices;
• Excellent problem-solving and decision-making abilities;
• Strong communication skills and the ability to lead cross-functional teams;
• Passion for mentoring and developing engineers.

Join us at Provectus to be a part of a team that is dedicated to building cutting-edge technology solutions that have a positive impact on society. Our company specializes in AI and ML technologies, cloud services, and data engineering, and we take pride in our ability to innovate and push the boundaries of what's possible.

As an ML Engineer, you’ll be provided with all opportunities for development and growth.

Let's work together to build a better future for everyone!
 

Requirements:

• Comfortable with standard ML algorithms and underlying math.
• Strong hands-on experience with LLMs in production, RAG architecture, and agentic systems
• AWS Bedrock experience strongly preferred
• Practical experience with solving classification and regression tasks in general, feature engineering.
• Practical experience with ML models in production.
• Practical experience with one or more use cases from the following: NLP, LLMs, and Recommendation engines.
• Solid software engineering skills (i.e., ability to produce well-structured modules, not only notebook scripts).
• Python expertise, Docker.
• English level - strong Intermediate.
• Excellent communication and problem-solving skills.
   

Will be a plus:

• Practical experience with cloud platforms (AWS stack is preferred, e.g. Amazon SageMaker, ECR, EMR, S3, AWS Lambda).
• Practical experience with deep learning models.
• Experience with taxonomies or ontologies.
• Practical experience with machine learning pipelines to orchestrate complicated workflows.
• Practical experience with Spark/Dask, Great Expectations.
   

Responsibilities:

• Create ML models from scratch or improve existing models. 
• Collaborate with the engineering team, data scientists, and product managers on production models.
• Develop experimentation roadmap. 
• Set up a reproducible experimentation environment and maintain experimentation pipelines.
• Monitor and maintain ML models in production to ensure optimal performance.
• Write clear and comprehensive documentation for ML models, processes, and pipelines.
• Stay updated with the latest developments in ML and AI and propose innovative solutions.

Join us at Provectus to be a part of a team that is dedicated to building cutting-edge technology solutions that have a positive impact on society. Our company specializes in AI and ML technologies, cloud services, and data engineering, and we take pride in our ability to innovate and push the boundaries of what's possible.

As an ML Engineer, you’ll be provided with all opportunities for development and growth.

Let's work together to build a better future for everyone!
 

Requirements:

• Comfortable with standard ML algorithms and underlying math.
• Strong hands-on experience with LLMs in production, RAG architecture, and agentic systems
• AWS Bedrock experience strongly preferred
• Practical experience with solving classification and regression tasks in general, feature engineering.
• Practical experience with ML models in production.
• Practical experience with one or more use cases from the following: NLP, LLMs, and Recommendation engines.
• Solid software engineering skills (i.e., ability to produce well-structured modules, not only notebook scripts).
• Python expertise, Docker.
• English level - strong Intermediate.
• Excellent communication and problem-solving skills.
   

Will be a plus:

• Practical experience with cloud platforms (AWS stack is preferred, e.g. Amazon SageMaker, ECR, EMR, S3, AWS Lambda).
• Practical experience with deep learning models.
• Experience with taxonomies or ontologies.
• Practical experience with machine learning pipelines to orchestrate complicated workflows.
• Practical experience with Spark/Dask, Great Expectations.
   

Responsibilities:

• Create ML models from scratch or improve existing models. 
• Collaborate with the engineering team, data scientists, and product managers on production models.
• Develop experimentation roadmap. 
• Set up a reproducible experimentation environment and maintain experimentation pipelines.
• Monitor and maintain ML models in production to ensure optimal performance.
• Write clear and comprehensive documentation for ML models, processes, and pipelines.
• Stay updated with the latest developments in ML and AI and propose innovative solutions.

Join us at Provectus to be a part of a team that is dedicated to building cutting-edge technology solutions that have a positive impact on society. Our company specializes in AI and ML technologies, cloud services, and data engineering, and we take pride in our ability to innovate and push the boundaries of what's possible.

As an ML Engineer, you’ll be provided with all opportunities for development and growth.

Let's work together to build a better future for everyone!
 

Requirements:

• Comfortable with standard ML algorithms and underlying math.
• Strong hands-on experience with LLMs in production, RAG architecture, and agentic systems
• AWS Bedrock experience strongly preferred
• Practical experience with solving classification and regression tasks in general, feature engineering.
• Practical experience with ML models in production.
• Practical experience with one or more use cases from the following: NLP, LLMs, and Recommendation engines.
• Solid software engineering skills (i.e., ability to produce well-structured modules, not only notebook scripts).
• Python expertise, Docker.
• English level - strong Intermediate.
• Excellent communication and problem-solving skills.
   

Will be a plus:

• Practical experience with cloud platforms (AWS stack is preferred, e.g. Amazon SageMaker, ECR, EMR, S3, AWS Lambda).
• Practical experience with deep learning models.
• Experience with taxonomies or ontologies.
• Practical experience with machine learning pipelines to orchestrate complicated workflows.
• Practical experience with Spark/Dask, Great Expectations.
   

Responsibilities:

• Create ML models from scratch or improve existing models. 
• Collaborate with the engineering team, data scientists, and product managers on production models.
• Develop experimentation roadmap. 
• Set up a reproducible experimentation environment and maintain experimentation pipelines.
• Monitor and maintain ML models in production to ensure optimal performance.
• Write clear and comprehensive documentation for ML models, processes, and pipelines.
• Stay updated with the latest developments in ML and AI and propose innovative solutions.

We are elai.io, an innovative AI-driven startup specializing in video generation.

Recently acquired by Panopto — a leader in interactive video solutions — we’re now part of a growing team of around 200 professionals focused on advancing learning through powerful, interactive video technology.

What You’ll Do as a Computer Vision Engineer:
1. Research, design and implement appropriate computer vision algorithms for the main product (generating video);
2. Research, find and use appropriate datasets;
3. Define quality metrics, run machine learning experiments, and analyse results;
4. Be on top of industry trends, research and propose new technologies.

Our ideal candidate has:
1. post-doc, PhD or Master’s degree in Computer Science or similar field;
2. proven experience as a Machine Learning Engineer or similar role;
3. deep knowledge of maths, probability, linear algebra, computer vision and algorithms;
4. 3+ years of experience with Python;
5. 2+ years of experience with PyTorch (TensorFlow experience is a plus);
6. familiarity with state of the art networks, architectures and models in computer vision area (like UNet, Resnet, GAN, Transformers, Diffusion Models, NeRF, etc.);
7. experience in deploying machine learning algorithms in production Base knowledge: git, docker, linux, bash;
8. experience in 3d graphics or game development would be a great plus.

We offer:
1. Opportunity to work with a highly qualified international and friendly team
2. Decent and timely payment fixed in USD
3. The most flexible work schedule, including remote work
4. Unlimited time off

We are looking for a Computer Vision Engineer with a background in classical computer vision techniques and hands-on implementation of low-level CV algorithms.

The ideal candidate will have experience with SLAM, Visual-Inertial Odometry (VIO), and sensor fusion.

We consider engineers at Junior/Middle/Senior levels — tasks and responsibilities will be adjusted accordingly.

Required Qualifications:

• 2+ years of hands-on experience with classical computer vision
• Knowledge of popular computer vision networks and components 
• Understanding of geometrical computer vision principles
• Hands-on experience in implementing low-level CV algorithms
• Practical experience with SLAM and/or Visual-Inertial Odometry (VIO)
• Proficiency in C++
• Experience with Linux
• Ability to quickly navigate through recent research and trends in computer vision.

Nice to Have:

• Experience with Python
• Familiarity with neural networks and common CV frameworks/libraries (OpenCV, NumPy, PyTorch, ONNX, Eigen, etc.)
• Experience with sensor fusion.

About the company

VReal Soft is a Ukrainian IT company with 7 years of experience building custom software solutions, mobile apps, and web platforms for clients in the US, Israel, and Europe. We are currently opening a position for a Data Extraction Specialist, combining project work in the healthcare domain with the opportunity for long-term in-house collaboration.

Position Summary

We are looking for a skilled Data Extraction Engineer / Document Automation Developer to help build a system that automatically extracts structured information from various medical and immunization records and stores it in a structured database format.
You’ll be working with diverse document formats (PDFs, scans, electronic forms), using OCR and NLP-based tools to process them.

Your responsibilities:

• Analyze medical document templates to identify key fields
• Develop pipelines for automatic extraction of fields such as:
  • Student Full Name
  • Date of Birth
  • Sex/Gender
  • Vaccination Information (e.g. Type, Date, Dose, Clinic, Manufacturer)
  • Next Due Dates (calculated from context or intervals)
     
• Build and integrate document processing flows using OCR or NLP tools such as Tesseract, Azure Form Recognizer, Amazon Textract, etc.
• Validate and store extracted data in a structured database
• Ensure accuracy and integrity of parsed data
• Collaborate with development and QA teams to integrate the solution into the main platform
   

Requirements:

• Hands-on experience with OCR tools:
  Tesseract, AWS Textract, Azure Form Recognizer, Google Document AI
• Strong knowledge of .NET / C#, especially for parsing documents and data transformation
• Understanding of NLP techniques and Regular Expressions
• Experience transforming unstructured data into structured formats
• Solid understanding of databases and storage formats (e.g. JSON, SQL)
   

Nice to have:

• Experience in the healthcare or education domain
• Familiarity with ML/AI-based approaches to document processing
• English proficiency for reading documentation and written communication
   

What we offer:

• Opportunity to work on a meaningful healthcare-related product
• Potential for long-term in-house cooperation after the initial project
• Flexible working hours
• Support and mentorship from a technical team
• Comfortable office in Cherkasy, or remote work option
• Internal training and English language development