Senior Machine Learning Scientist - Credit Card Transaction Data

Analytic Recruiting Inc.; New York (NY); Remote; USD 180,000 - 230,000; Full time

Job summary

Analytic Recruiting Inc. in the United States is seeking a Senior Machine Learning Scientist focused on merchant and transaction data to join its data science organization.

You will lead R&D, design and deploy end-to-end production ML systems, and collaborate with data engineering and product teams to transform messy transaction data into high-quality data products. You will apply multiclass classification, NLP, and transformer-based architectures, translating complex business problems into

Qualifications

• Extensive experience leading end-to-end production ML projects.
• Strong expertise in multiclass classification and Transformer-based architectures.
• Experience with financial services data, especially credit/debit card transactions.
• Solid Python and SQL skills with production-quality coding experience.
• Deep NLP knowledge including BERT/LLMs and entity resolution.

Responsibilities

• Research, prototype, and deploy new ML models, including LLM-based approaches.
• Build end-to-end production ML pipelines from data ingestion to deployment and monitoring.
• Develop metrics, evaluation frameworks, and data quality measures for model outputs.
• Mine large-scale credit/debit card transaction data to identify ML opportunities.
• Serve as an internal ML expert, collaborating with cross-functional teams and clients.
• Communicate methodologies and results to both technical and non-technical audiences.

Skills

End-to-end ML production

Multiclass classification

NLP

Python

SQL

Transformer models

Education

Advanced degree

Tools

Redshift

Snowflake

BigQuery

Job description

Senior Machine Learning Scientist – Merchant & Transaction

Our client, a leading data driven financial technology company is seeking a Senior Machine Learning Scientist to join its advanced Data Science organization. We are looking for a highly skilled ML expert with deep experience in multiclass classification, credit/debit card transaction data, and end-to-end production machine learning systems. This role is ideal for someone who thrives on transforming messy, semi structured partner data into high quality structured data products at scale

REMOTE ROLE

Responsibilities

• Conduct R&D to propose, experiment with, and deploy new ML models, including LLM based approaches
• Build and optimize end-to-end production ML pipelines, from data ingestion through deployment, monitoring, and continuous improvement
• Develop metrics, evaluation frameworks, and quality measurement systems to ensure high accuracy model outputs
• Mine large scale consumer datasets, including credit and debit card transaction data to identify new ML opportunities and data product innovations
• Serve as an internal ML expert, supporting cross functional teams, clients, and stakeholders
• Communicate methodologies, findings, and results to technical and non-technical audiences

Requirements

• Extensive experience leading end-to-end production ML projects, including model development, deployment, monitoring, and optimization
• Strong expertise in multiclass classification, including model design, evaluation, and productionalization using modern ML like Transformer‑based architectures, encoder models, for classification.
• Experience working with financial services data, especially credit card and debit card transaction data
• Deep knowledge of machine learning and statistical fundamentals, with the ability to translate business problems into practical ML solutions
• Strong background in NLP (classification, entity extraction, entity resolution) and familiarity with models such as BERT, LLMs, and classical NLP techniques
• Solid software engineering and data engineering skills; expert in Python and SQL with experience writing production quality code
• Experience working with cloud data warehouses (e.g., Redshift, Snowflake) and data lakes
• Advanced degree in Statistics, Mathematics, Computer Science, Economics, or a related field, plus 5+ years of industry experience