PayU

Data Scientist

Job description

We are looking for a highly skilled Data Scientist to join our team at PayU.

As a Data Scientist, you will develop complex payment models, analyze financial data, uncover insights about merchants, shoppers and issuers.

You will identify opportunities by leveraging statistical, algorithmic, mining, and visualization methods.


At PayU you will have the opportunity to create tools and solutions that will save time and resources, increase revenue and build stronger relationships of the participants.

The ideal candidate will have exceptional analytical and problem-solving skills, as well as a passion for creating value beyond the technical responsibilities of a Data Scientist.

Interested in using data-driven insights to solve complex business problems, and able to think creatively and collaboratively, join us!


Key Responsibilities

  • Develop machine learning models that drive actionable insights to support business decisions.
  • Build and deploy machine learning applications that enable automation and optimization across various business domains like recomendations, anomaly detection, classification.
  • Collaborate with cross-functional teams to identify opportunities for data-driven decision making and drive the adoption of machine learning and artificial intelligence across the organization.
  • Working with large and complex datasets from various internal and external sources.
  • Staying up-to-date with new data acquisition techniques and incorporating new data sources into analyses as needed.
  • Stay up-to-date with the latest trends and techniques in machine learning and AI.


Requirements

  • Bachelor's degree in engineering, mathematics, statistics, computer science or a related field.
  • 5+ years of experience in machine learning and artificial intelligence
  • Strong programming skills in Python,
  • Proficient in SQL and experience with data warehousing and data architecture design.
  • Experience with cloud technologies such as AWS, Azure, or GCP.
  • Strong understanding of statistical modeling techniques and data analysis methods, including supervised and unsupervised learning, deep learning, and NLP.
  • Excellent communication skills and ability to collaborate effectively with cross-functional teams, including data engineers, product managers, and business stakeholders.
  • Proven ability to work independently and manage multiple projects simultaneously.

What we offer:

  • Work in an international organization operating in a rapidly changing industry
  • Full-time employment under a contract of employment
  • Benefits: ability to develop one’s own package in MyBenefit system
  • Series of training
  • Friendly work atmosphere in a young cooperation-driven team
  • Ability to work in a hybrid model after probation period


Our work environment:

  • A diverse working environment within a multicultural setting
  • An inclusive environment that ensures we listen to a diverse range of voices when making decisions
  • A positive, get-things-done workplace
  • A dynamic, constantly evolving space (change is par for the course – important you are comfortable with this)
  • Ability to learn cutting edge concepts and innovation in an agile start-up environment with a global scale
  • A democratic work environment where you can drive your outcomes


About us:

At PayU, we are a global fintech investor and our vision is to build a world without financial borders where everyone can prosper. We give people in high-growth markets the financial services and products they need to thrive. Our expertise in 18 high-growth markets enables us to extend the reach of financial services. This drives everything we do, from investing in technology entrepreneurs, to offering credit to underserved individuals, to helping merchants buy, sell and operate online. Being part of Prosus, one of the largest technology investors in the world, gives us the presence and expertise to make a real impact.

Find out more: https://corporate.payu.com/wp-content/uploads/2022/09/Become-A-PayUneer_PayU-candidate-deck.pdf

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