Data Science Services

We are offering leading end-to-end data solutions that will help you make the best business decisions, improve user experience, and turn your big vision into reality. Your dreams. Our expertise. Together, we give you the strength to succeed.

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What Is Data Science?

Data science is a combination of math and statistics, specialized programming, advanced analytics, artificial intelligence (AI), and machine learning. It is used to reveal the insights hidden in an organization’s data.

Insights that Data Science brings can be used by decision makers as a guide for strategic planning, and thus help them realize their business’ full potential.

Data Science as a Service

Data Science services provide invaluable insights for making business decisions by using statistical methods and machine learning algorithms to further analyze data and create predictive models.

The main goal of the Data Science team is to use those insights to help clients answer some of the burning questions like:

  • What direction do they want to develop their business?
  • What is their primary goal?
  • What are the limitations to achieving that goal?
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Who We Are

Data Science Roles

The core roles of our Data Science team are Data Scientist, Data Engineer, and Data Analyst. These three roles combine technical expertise and domain knowledge with solid understanding of clients' business goals to provide data solutions that will help them succeed.

Wondering what are the key differences between these roles? Read more below:

Data Scientists 

To avoid making important business decisions based on "gut feeling", there are Data Scientists. Data scientists use statistical methods, machine learning algorithms and other tools to analyze data and create predictive models. They are the core members of a team who make decisions based on statistical conclusions obtained from historical data.

Data Engineers

Data engineers are in charge of developing, testing and maintaining data pipelines. 

Data Analysts

Data Analysts analyze and interpret numeric data, and they build dashboards to help companies make better, data-driven decisions.

Data Science Areas in which we are experts

  • Big Data
  • Forming Data Warehouses & Data Lakes
  • ETL processes
  • Computer Vision
  • Deep Learning
  • Machine Learning
  • Recommender Systems
  • Linear Programming
  • Reinforcement Learning
  • Time Series Analysis
  • A/B Testing
  • Analysis of Graphs and Graph Neural Networks
  • NLP
  • Data Visualisations and Dashboard
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Why Choose Vega IT for Data Engineering, Data Science and Data Analytics?

When you combine our relentless passion with domain and technical expertise we have been gathering since 2008, you get a team that can utilize previous knowledge to better understand your vision, customers, specific industries' requirements, and the challenges you are facing.

We work at the cutting-edge of digital product development - helping clients turn their vision into reality. Our flexible service model is designed to fit your needs, whether you need a couple of engineers to expand your capacity, or a whole product team to ship the next big thing.

If you need a team of passionate experts to bring your vision to life, you can rely on us to deliver.

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Data Science Technologies we use:

  • Python
  • PySpark
  • Data Scraping Stack: Scrapy, Selenium, BeautifulSoup
  • Data Analysis Stack: Pandas, Numpy, Matplotlib, Seaborn, NetworkX
  • Machine Learning Stack: Scikit-Learn, XGBoost, FBProphet, CatBoost
  • Deep Learning Stack: PyTorch, Keras, Tensorflow
  • NLP Stack: NLTK, HuggingFace, Stanford CoreNLP, Gensim
  • Data Analytics Stack: PowerBI, Tableau
  • Database Stack: SQL, MongoDB, FastAPI, Flask, Docker, OpenCV
  • Azure Stack: DataBricks, Azure Functions, Azure AI services (e.g. LUIS, Speech to Text), Data Factory, Data Lake, Delta Lake, Cosmos DB, Synapse, Data Explorer, ML Studio
  • AWS Stack: Sagemaker, Glue, Kinesis, S3, EC2, EMR, AI Services (e.g. Translate, Text to Speech, Rekognition), Redshift, RDS, Athena, Quicksight, Lambda, DocumentDB, Neptune, Elasticsearch, Kibana, MLFlow, Grafana

Data Engineering Technologies we use:

  • Python
  • Golang
  • Java
  • SQL
  • AWS Stack: Redshift, Dynamo, RDS, ECS, EC2, Lambda, SimpleQueueService, CodePipeline...
  • Azure: SQL Database, Cosmos DB, Data Lake, Data Factory, Functions, Databricks...
  • Apache tools: Airflow, Spark, Kafka, Hadoop...
  • Terraform
  • Snowflake
  • Elasticsearch

Unsere Stärke in Zahlen

16 +
Jahre auf dem Markt
750 +
Experten
1500 +
durchgeführte Projekte
200 +
Kunden, die uns vertrauen

Case Study: Argus Data Insights

The client is a company that processes data collected from the media and finds insights within that data. Our goal was to use Natural Language Processing (NLP) backend services to improve solution performance and accuracy. Find out more.

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Our Process

Get to know us, our work methodology and our company culture. We know that there’s no “one-size-fits-all” solution when it comes to software development. This is why we want to learn more about your project’s needs to match you with the right software developers from our 750+ professionals.

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What wir tun

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Software-Produktentwicklung

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Engagiertes Entwicklungsteam

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Salesforce

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Massgeschneiderte Softwareentwicklung

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Embedded Software Entwicklung

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Webseitenentwicklung

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Entwicklung von mobilen Apps

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Adobe Experience Manager-Entwicklung

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Umbraco

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Hybride mobile App-Entwicklung

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iOS app development

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Forschung und Entwicklung

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Entwicklung von Unternehmenssoftware

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Frontend-Entwicklung

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Which business model suits you?

Different budgets, deadlines, challenges, and requirements. There is no one-size-fits-all approach to software development. To match your exact goals and ambitions, we offer two types of business models:

  • Time & material: Greater control. Flexibility. Participation in candidate selection. With no rigid processes or end dates, this business model is easier to scale up or down as your business needs change.
  • Fixed price: Fixed scope. Fixed budget. Fixed timeline. Those are the main benefits of the fixed price model. You set the requirements upfront, and we deliver the project within them.

Many clients choose to start with the fixed-price model. However, as their project scope evolves, they typically shift to the time & material model.

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We’re here to find fast, elegant solutions to your trickiest problems.

Co-Founder & CEO Sasa Popovic

Saša gründete Vega IT vor 15 Jahren zusammen mit seinem ehemaligen Mitbewohner Vladan an der Universität. Ihr Traum, ein IT-Unternehmen zu gründen, hat sich zum führenden Softwareentwicklungsunternehmen mit mehr als 350 Entwicklern in Serbien entwickelt. Wenn Sie lieber eine E-Mail senden möchten, wenden Sie sich bitte an sasa.popovic@vegait.de.

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