Finding a professional data science service provider that could turn your raw big data into profound business insights is a challenging task. In the US and Europe, you are going to face a shortage of experts in this field. Thus it’s worth considering outsourcing big data analytics to a country with a large talent pool and a big number of providers. One of the most attractive destinations in this respect is Ukraine. Over the last years, this developing Eastern European country has taken the lead in IT outsourcing. Today Ukraine has over 100,000 IT professionals that provide best in class software development including data science outsourcing services .
We’ve gathered information on the Ukrainian IT outsourcing firms that offer expertise in big data analytics and related fields. So this article gives a brief review of the seven established Ukrainian IT vendors that have excellent track record as data science service providers.
7 best data science service providers in Ukraine
1. N-iX
N-iX is a global software engineering company with 24 years in the market and 2,400 specialists, including 200 data, AI, and Machine Learning experts. Headquartered in Malta, the company runs delivery centers across Ukraine, Poland, and other European locations, with offices in the US and Latin America.
The data engineering services cover data platform design, pipeline development, analytics, and machine learning, built on Apache Spark, Databricks, Snowflake, BigQuery, Synapse Analytics, Kafka, and Kubernetes. N-iX engineers work in Python, Scala, and SQL across AWS, Azure, and Google Cloud.
The company has delivered data projects for Gogo, a global in-flight connectivity provider, and for Lebara, a multinational MVNO, where it built a data lake and rebuilt reporting.
2. GlobalLogic
Part of the Hitachi group since 2021, this company was built on Ukrainian engineering centers and still runs delivery sites in Ukraine alongside Poland, Romania, Slovakia, and Croatia, with around 34,000 people across all locations. Its data practice covers data platform engineering, analytics, and AI, concentrated in automotive, telecommunications, healthcare, and media. The company also does embedded and product engineering, which shows in how its data teams handle high-volume sensor and telemetry workloads.
3. Avenga
Formed in 2019 through the merger of four companies, this vendor employs around 6,000 people with delivery centers in Ukraine, Poland, Germany, and Latin America. Its data practice covers data engineering, analytics, business intelligence, and machine learning, with particular focus on life sciences, financial services, and automotive. Avenga works with enterprise clients across Europe and North America, combining data work with its CRM and custom software practices.
4. Sigma Software
Founded in 2002 and operating from Ukraine and Sweden, this vendor employs around 2,000 specialists with delivery centers across Ukraine, Poland, Czechia, Bulgaria, Sweden, and Portugal. Its data practice covers Big Data consulting, real-time analytics, data platforms for predictive analytics, BI reporting, data warehouses, and data lakes. The company builds solutions for automotive, advertising technology, aviation, gaming, and education, and holds a 4.8 rating on Clutch.
5. Ciklum
Founded in Denmark in 2002 and built on Ukrainian engineering teams, Ciklum employs around 4,000 specialists across Ukraine, Poland, Spain, India, and the UK. Its data and AI practice covers data strategy, data platform engineering, analytics, and machine learning, with work concentrated in retail, healthcare, financial services, and media. The company works with enterprise clients across Europe and North America and holds a 4.8 rating on Clutch.
6. Grid Dynamics
Listed on NASDAQ and headquartered in California, this vendor runs European delivery centers in Ukraine, Poland, Serbia, Moldova, and Armenia, with roughly 2,700 engineers. Data engineering, analytics, and AI sit at the center of its positioning instead of alongside a broad services list. Most of its work is in retail and e-commerce, alongside financial services and manufacturing, and the company publishes detailed engineering case studies on the data platforms it builds.
7. SoftServe
Founded in Lviv in 1993 and now headquartered in Austin, Texas, SoftServe employs around 10,000 specialists, with Ukrainian delivery centers alongside sites in Poland, Romania, Bulgaria, and Spain. Its data practice covers data strategy, data platform engineering, analytics, BI, machine learning, and generative AI. The company holds premier partner status with AWS, Google Cloud, and Microsoft Azure, and works with clients in financial services, healthcare, retail, manufacturing, and energy.
Summing up
Selecting a data science service provider in Ukraine, you are going to consider a number of companies. The thing is, the country has a variety of IT outsourcing vendors that offer data mining, big data analytics, and machine learning services. They differ in size, cooperation style, technological expertise, specific domain knowledge etc. Still, the experience in data science projects development for your particular industry should be the main factor to consider. We advise choosing a company with a broad analytic tech stack and a decent portfolio of data science projects. We hope, our review will help you find a partner that will turn your raw data into actionable knowledge. No doubt, your business will succeed from the cooperation with one of the Ukrainian data science service providers .
This article uses materials collected from companies’ corporate websites and LinkedIn profiles.
FAQ
How many IT specialists does Ukraine have?
Ukraine’s IT industry employs more than 305,000 specialists, and computer services exports reached $3.34B in the first half of 2026, up 4.1% year on year. The United States accounts for around 37% of that export volume, which gives most vendors established experience working with North American clients.
How do Ukrainian vendors handle GDPR and data protection?
Ukrainian vendors deliver for EU and UK clients under GDPR, so data processing agreements, access controls, and retention policies are standard practice. For regulated work, ask where data is stored and processed, whether any of it leaves the EU, and which certifications the vendor holds, typically ISO 27001 and SOC 2.
What is the difference between data science and data engineering services?
Data engineering builds the pipelines, platforms, and storage that make data usable. Data science applies models to that data to produce forecasts, classifications, and recommendations. Most enterprise projects need both, and engaging a data science team before the engineering foundation exists is the most common sequencing mistake in these projects.
