ML Engineer (classic ML)

Описание вакансии

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:

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.