Contact us to get started!
Lead Data Scientist
Bitola, Macedonia
Full-time
Hybrid
About the role
PaymentIQ is building a dedicated data team in Bitola with a clear purpose: to leverage large-scale transaction data and turn it into actionable intelligence. As a Lead Data Scientist, you will take ownership of building fraud detection and anomaly detection capabilities from the ground up, while guiding the team in experimentation, model development, and delivery.
This is a greenfield opportunity where no existing models are in place yet. You will define direction, select approaches, and ensure that data science efforts translate into real product value.
Key responsibilities
- Lead the design and development of fraud detection and anomaly detection models
- Work with large-scale payment transaction data to identify patterns and risks
- Define and guide experimentation with machine learning models
- Collaborate with Data Engineers on data pipelines and data availability
- Align closely with Product on roadmap items and priorities
- Translate business problems into data science solutions
- Support and mentor team members as the team grows
- Contribute hands-on to model development and validation
Requirements
- Around 5 years or more experience in data science or machine learning
- Strong experience with Python and common data science libraries
- Experience with anomaly detection, fraud detection, or similar domains is preferred
- Experience working with large datasets in production environments
- Understanding of data pipelines and working with structured and unstructured data
- Experience with AWS infrastructure as a foundation for building and deploying data science solutions
- Ability to work in a greenfield setup with limited predefined structure
- Strong problem-solving mindset and ownership
- Excellent English skills
Nice to have
- Experience in payments, fintech, or iGaming
- Exposure to real-time or near real-time data processing
- Experience working in cross-functional teams with product and engineering
Why join us?
- Ownership of a new data science capability within PaymentIQ
- Direct impact on fraud prevention and product intelligence
- Opportunity to shape a team from an early stage
- Collaboration with international engineering and product teams
- Company-provided equipment, MacBook.
- Standard working hours aligned with European time zones.
Send us your resume
Our core values
Latest equipment
Get the hardware and software you need to do your best work.
Competitive compensation
Market-rate salary, equity, and performance bonuses.
Hybrid working model
50% in office, the rest remote, supporting a healthy work–life balance
Ownership
Meaningful work with production impact across hundreds of merchants and 300+ PSPs.
Contact us to get started!
Lead Data Scientist
Bitola, Macedonia
Full-time
Hybrid
About the role
PaymentIQ is building a dedicated data team in Bitola with a clear purpose: to leverage large-scale transaction data and turn it into actionable intelligence. As a Lead Data Scientist, you will take ownership of building fraud detection and anomaly detection capabilities from the ground up, while guiding the team in experimentation, model development, and delivery.
This is a greenfield opportunity where no existing models are in place yet. You will define direction, select approaches, and ensure that data science efforts translate into real product value.
Key responsibilities
- Lead the design and development of fraud detection and anomaly detection models
- Work with large-scale payment transaction data to identify patterns and risks
- Define and guide experimentation with machine learning models
- Collaborate with Data Engineers on data pipelines and data availability
- Align closely with Product on roadmap items and priorities
- Translate business problems into data science solutions
- Support and mentor team members as the team grows
- Contribute hands-on to model development and validation
Requirements
- Around 5 years or more experience in data science or machine learning
- Strong experience with Python and common data science libraries
- Experience with anomaly detection, fraud detection, or similar domains is preferred
- Experience working with large datasets in production environments
- Understanding of data pipelines and working with structured and unstructured data
- Experience with AWS infrastructure as a foundation for building and deploying data science solutions
- Ability to work in a greenfield setup with limited predefined structure
- Strong problem-solving mindset and ownership
- Excellent English skills
Nice to have
- Experience in payments, fintech, or iGaming
- Exposure to real-time or near real-time data processing
- Experience working in cross-functional teams with product and engineering
Why join us?
- Ownership of a new data science capability within PaymentIQ
- Direct impact on fraud prevention and product intelligence
- Opportunity to shape a team from an early stage
- Collaboration with international engineering and product teams
- Company-provided equipment, MacBook.
- Standard working hours aligned with European time zones.
Send us your resume
Our core values
Latest equipment
Get the hardware and software you need to do your best work.
Competitive compensation
Market-rate salary, equity, and performance bonuses.
Hybrid working model
50% in office, the rest remote, supporting a healthy work–life balance
Ownership
Meaningful work with production impact across hundreds of merchants and 300+ PSPs.
Contact us to get started!
Lead Data Scientist
Bitola, Macedonia
Full-time
Hybrid
Lead Data Scientist
Data Engineer
Bitola, Macedonia
Full-time
Hybrid
About the role
PaymentIQ is building a dedicated data team in Bitola with a clear purpose: to leverage large-scale transaction data and turn it into actionable intelligence. As a Lead Data Scientist, you will take ownership of building fraud detection and anomaly detection capabilities from the ground up, while guiding the team in experimentation, model development, and delivery.
This is a greenfield opportunity where no existing models are in place yet. You will define direction, select approaches, and ensure that data science efforts translate into real product value.
Key responsibilities
- Lead the design and development of fraud detection and anomaly detection models
- Work with large-scale payment transaction data to identify patterns and risks
- Define and guide experimentation with machine learning models
- Collaborate with Data Engineers on data pipelines and data availability
- Align closely with Product on roadmap items and priorities
- Translate business problems into data science solutions
- Support and mentor team members as the team grows
- Contribute hands-on to model development and validation
Requirements
- Around 5 years or more experience in data science or machine learning
- Strong experience with Python and common data science libraries
- Experience with anomaly detection, fraud detection, or similar domains is preferred
- Experience working with large datasets in production environments
- Understanding of data pipelines and working with structured and unstructured data
- Experience with AWS infrastructure as a foundation for building and deploying data science solutions
- Ability to work in a greenfield setup with limited predefined structure
- Strong problem-solving mindset and ownership
- Excellent English skills
Nice to have
- Experience in payments, fintech, or iGaming
- Exposure to real-time or near real-time data processing
- Experience working in cross-functional teams with product and engineering
Why join us?
- Ownership of a new data science capability within PaymentIQ
- Direct impact on fraud prevention and product intelligence
- Opportunity to shape a team from an early stage
- Collaboration with international engineering and product teams
- Company-provided equipment, MacBook.
- Standard working hours aligned with European time zones.
Send us your resume
Benefits & Perks
Latest equipment
Get the hardware and software you need to do your best work.
Competitive compensation
Market-rate salary, equity, and performance bonuses.
Hybrid working model
50% in office, the rest remote, supporting a healthy work–life balance
Ownership
Meaningful work with production impact across hundreds of merchants and 300+ PSPs.
