ML Data Scientist, Payments

eBay

4 - 9 years

32 - 40 Lacs

bengaluru

Posted:-1 days ago| Platform:

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Skills Required

computer science computer vision data analysis prototype publishing query optimization machine learning data mining sql python

Work Mode

Work from Office

Job Type

Full Time

Job Description

What you will accomplish:

Build , Train and deploy ML models for intelligent payment routing, personalization, and intelligent decisioning in payments.
Perform feature engineering, data preprocessing, and large-scale data analysis.
Research, design, and implement novel machine learning and AI algorithms across areas such as deep learning, generative models, reinforcement learning, NLP, or computer vision.
Design, train, and optimize machine learning models for a variety of business applications (classification, regression, recommendation, and personalization).
Construct robust ML pipelines for training, validation, and deployment using modern ML stacks.
Apply prompt engineering techniques with Generative AI models (LLMs, diffusion models, etc.) to tackle application-driven problems.
Leverage vector databases and build/optimize embeddings for search, retrieval, and semantic understanding.
Conduct large-scale experiments, develop benchmarks, and evaluate new approaches against existing solutions.
Stay at the forefront of ML research, proactively identifying emerging techniques that can create business and product advantages.
Knowledge Sharing: Contribute to internal technical discussions, mentoring, and sharing research insights with engineering teams.
Prototype new approaches and publish in leading ML conferences/journals when applicable.
Collaborate with engineers and product teams to build robust ML-powered applications.

What You Will Bring:

4 + Years of applied research experience in machine learning or AI
Proficiency in Python and ML libraries/frameworks (e.g., PyTorch, TensorFlow, JAX).
Strong mathematical and algorithmic background (optimization, probability, statistics, linear algebra).
Solid foundation in statistics, predictive modeling, and information retrieval.
Experience with large-scale experimentation, distributed training, and working with big data systems.
Familiarity with real-world applications such as LLM, NLP, computer vision, or recommendation systems.
Knowledge of statistical techniques including regression, time series analysis, hypothesis testing, combining disparate data sources.
Expertise with applying predictive modeling techniques, statistics and information retrieval methods to real-world data
Hands on experience with SQL/Hive/Spark, data mining and big data query optimization
Extensive experience with large data sets and data manipulation.
Excellent problem-solving skills and experience in deploying predictive models in production environments.

Education: MS or Bachelor s in Computer Science, Machine Learning, Statistics, or related field

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