Senior Data Scientist

To strengthen Paylead’s capabilities in bank transaction analysis for banks and merchants, we are looking for a SeniorMachine Learning Engineer whose missions will include:

• Review existing Data Science and ML algorithms and continuously improve them

• Propose and experiment with new ML‑based solutions to tackle real‑life business problems

• Build ML algorithms and data pipelines with a strong focus on robustness, scalability, and compliance

• Deploy, monitor, and scale ML algorithms across all Paylead use cases (internal and external)

You'll be part of a multidisciplinary, experienced squad of 6 engineers

• At least 4years of professional experience in Machine Learning

  • Excluding internships and academic projects only

  • Experience on challenging, state‑of‑the‑art ML topics

• Strong engineering or scientific background, such as:

  • Engineering degree with a major in statistics / data science / ML

  • Or Master’s degree in mathematics, statistics, data science, or machine learning

• Data Analysis oriented mindset

  • Abilty to produce hypothesis and to build a plan to test them until deploying them to production

  • Experience on production environment, you have a track record on delivering working features in production

  • Model monitoring and run

• Deep understanding of Machine Learning

  • Knows how the models work internally

  • Solid grasp of the mathematics behind ML models

  • Hands‑on experience with ML use cases such as prediction and recommendation systems

• Strong Python skills, with experience in common ML / data libraries (Pytorch, Polars, Sklearn)

• Solid SQL skills

• Comfortable with Bash / CLI, Git, and Docker

Nice to have

• Experience with Rust

• First exposure to infrastructure topics (deployment, monitoring, cloud, etc.)

• Genuine passion for Data Science, Data Exploration and Machine Learning

• Strong team player

• Business and product mindset: able to understand use cases, constraints, and impact

• Willingness to go the extra mile when needed

• Clear, structured communication (both spoken and written)

Nice to have

• Contributions to open‑source projects or significant personal projects

• Strong writing skills, including documentation for internal and external audiences

• Screening with CTO

• Tech interview with ML Engineers

• Open discussion with the squad