Our vision is to fundamentally Reshape Revenue Management by Augmenting revenue decisions and Empowering the Business world to focus on Strategy.
Our team provides Platform-as-a-service…
Our vision is to fundamentally Reshape Revenue Management by Augmenting revenue decisions and Empowering the Business world to focus on Strategy.
Our team provides Platform-as-a-service…
Headquarters / legal: Revenue.AI B.V.; based in the Netherlands
Product: AI-driven pricing and revenue management SaaS platform (PaaS) with industry modules
Founder / CEO: István Czilik
Team size: Approximately 27 employees
Funding signal: Crunchbase records one funding round; Peachscore listed as investor
Company Overview
Problem Domain
Pricing, revenue management, promotion optimization and data unification for industries such as CPG, commodity trading, B2B manufacturing, retail and veterinary/health.
Industry
SaaS — Pricing & Revenue Management / AI
Funding Track Record
Crunchbase lists one funding round and lists Peachscore as an investor; detailed amount and date are not publicly available in provided evidence.
Investor Signal
“Peachscore listed as an investor on Crunchbase”
Founders
What we do
Join the Team
Data Scientist
HybridBelgrade, RS
Hybrid • Belgrade, RS
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Location: Belgrade and Budapest
We are looking for a
Data Scientist
who collaborates with a team of professionals to gather business, architectural, and non-functional requirements, subsequently translating these into robust, scalable, and operational analytical solutions that integrate seamlessly with the overall data architecture. The individual will design applications based on the identified architecture, technology landscape, IT standards, and enterprise roadmaps. Additionally, this role involves supporting design implementation by addressing complex technical challenges encountered by the project team throughout the entire development lifecycle.
Role overview
Identify business problems.
Find the appropriate data and methods to address these problems.
Build and validate analytical models.
Present findings in a clear and informative manner.
Analyze large volumes of structured and unstructured customer data using advanced analytical solutions.
Utilize various mathematical and econometric models to develop descriptive and predictive models that support better decision-making.
Transform analyzed data into actionable insights and business value.
Present results to all management levels.
Create high-quality data visualizations.
Communicate effectively with different departments and roles, such as product managers and engineers, to discuss complex data-driven findings and technical issues.
Educate and train others on data science-related topics.
Estimate, plan, and coordinate the delivery of large projects using the Scrum framework.
Create a data science solution architecture.
Propose holistic data science solutions for customer problems.
We believe that you’ll enjoy this role if you have
Aptitude for problem solving
Excellent communication and teamwork skills
Great attention to detail
Familiarity with Agile frameworks
Startup experience
Remote work experience
What you’ll need to be successful
Familiarity with at least one of these domains: CPG, Retail, and Commodity Trading.
Cloud: Azure – Storage; Compute; Notebooks; Data Catalogs
CI/CD principles & tools (e.g. Jenkins)
Version Control Systems (e.g. Git)
Benefits of joining us
You will share a next-generation vision and mission through our revolutionary, Digital Assistant for Revenue Management. You will have a purposeful job in our fast-growing environment where we will build something amazing together!
Even when you work hard, you will still have time for your personal life due to flexible working hours based on core time.
You will work in a flat and flexible organization where every team member has access to any team member. Working on exciting projects independently, while closely connected with leading, super cool and talented international experts encourages everyone to think outside the box and gain new experiences.
You will have the collaboration and support of the team whenever you need it.
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Familiarity with NLP/text mining (text quality and cleansing, similarity measures, fuzzy matching methodologies).
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