Machine Learning Engineer (Risk)

Bengaluru, Karnataka, India

Weekday

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This role is for one of the Weekday's clients

Salary range: Rs 3000000 - Rs 6000000 (ie INR 30-60 LPA)

Min Experience: 5 years

Location: Bengaluru

JobType: full-timeWe are looking for a Machine Learning Engineer (Risk) to develop and implement cutting-edge machine learning solutions for complex risk-related challenges. You will analyze large datasets, detect patterns, and build scalable models to enhance fraud detection and risk assessment. This role requires a deep understanding of the machine learning lifecycle, including algorithms, data structures, and system design.

Requirements

Key Responsibilities

🔹 Develop & Optimize ML Models

  • Design, develop, and implement machine learning algorithms to solve risk-related challenges.
  • Leverage data-driven insights to enhance fraud detection and risk assessment capabilities.

🔹 Data Processing & Analysis

  • Identify and apply appropriate techniques to process and analyze large datasets (both labeled and unlabeled).
  • Extract valuable insights to improve risk models and decision-making.

🔹 System Enhancement & Performance Tuning

  • Conduct performance analysis, scaling, tuning, and optimization of ML models.
  • Review and enhance software and system architecture for stability and efficiency.

🔹 Cross-Functional Collaboration

  • Provide technical support across different areas of the system, beyond just ML applications.
  • Work closely with engineering, data, and risk teams to build scalable solutions.

🔹 Research & Development

  • Explore and implement innovative approaches in fraud detection and risk modeling.
  • Stay up to date with the latest advancements in machine learning, credit risk modeling, and fraud detection.

Requirements

Bachelor’s degree in Computer Science, Information Systems, or related fields with a specialization in Machine Learning.
Strong foundation in databases (MySQL, NoSQL, Columnar databases) and data scaling techniques.
Hands-on experience with Machine Learning algorithms and their real-world applications.
Proficiency in programming languages such as Python, C++, and C.
Mandatory experience in Credit Risk, Unsupervised Modeling, and Fraud Modeling.
Experience in the e-payments or e-commerce industry is a plus.
Excellent analytical, communication, and problem-solving skills.

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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

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Tags: Architecture Computer Science Credit risk E-commerce Engineering Machine Learning ML models MySQL NoSQL Python R&D Research

Region: Asia/Pacific
Country: India

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