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ML Engineer (classic ML)

zypl.ai

zypl.ai

Software Engineering, Data Science
Uzbekistan
Posted on Wednesday, July 10, 2024
ML Engineer (classic ML)

Job Title: ML Engineer

Level: Middle+ / Senior I

Location: Remote (GMT±3) or hybrid (Astana KZ, Dushanbe TJ, Khujand TJ, Tashkent UZ)

Salary: to be discussed

Job Summary:

We are a Dubai based provider of SaaS tailored credit scoring solutions for more than 30 financial institutions across 10 markets. In a nutshell, we are looking for a ML Engineer who is going to develop ML models for financial industry from 0 to deployment (not necessarily all the skills must be present — we can help you grow). Ideally, the candidate has a background in credit risk modeling in a leading financial institutions or worked as a risk analyst / validation expert at Big4

About us on media

News: ARCET Global AI Series (Best Use of AI in Risk), Plug and Play Investment

Accelerators: Fintech Hive Accelerator (DIFC, Dubai), MISK Accelerator (Plug and Play x Mohammed Bin Salman Foundation), Astana Hub Google for Startups

We expect that you are able to:

  • Technical expertise:Bring a good conceptual understanding of ML pipelines development stages (data preprocessing, modelling, validation, deployment).
  • Demonstrate proficiency in classic machine learning algorithms, including but not limited to classic ML (linear regression, decision trees) and neural networks.
  • Ability to read and write reproducible and optimal Python code.
  • Effective Communication:Show excellent written and verbal communication skills in English.
  • Translate technical concepts into layman's terms for clients and stakeholders.
  • Collaborate effectively with cross-functional teams, including back/front-end developers, and DevOps
  • Pitch results and our software to potential clients
  • Knowledge of Credit Risk, Financial Institutions, and Fintech:In-depth understanding of credit risk assessment methodologies and best practices in the financial industry.
  • Familiarity with financial institutions' operations, compliance, and regulatory requirements.

Preferred background:

  • Proven experience in machine learning / data science roles (2-3 years);
  • Bachelor's or Master's degree in Computer Science, Data Science, Economics or other quantitative field;
  • Great knowledge of classic Machine Learning (models, metrics, validation etc.);

Tech Requirements:

Our stack: Python, MLFlow, Azure Cloud, Docker, Github, MySQL

  • Python: you know how to write reproducible and clear notebooks, but prefer to go with .py files 🙂;
  • Good knowledge of Git workflow;
  • Know how to work with cloud services Azure/AWS;
  • (Optional) Basic knowledge of Docker, MLFlow
  • Application Instructions: To apply, please send your CV to hr@zypl.ai and in the subject line of the letter indicate the position for which you are applying.

    Upon successful passage of the pre-selection stage (CV review), you will partake in a first-round online interview in behavioral format, and if successful, a second-round work-sample test. We promise to reply to each candidate with a definitive response within five days at each stage.