Senior Machine Learning Scientist - Credit Card Transaction Data

Posted 2 days ago

analytic recruitingNew York (NY)

SENIORITY

Senior

Apply

About the role

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 scaleREMOTE ROLEResponsibilities 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 Preferred Qualificationsconsumer spend analytics

Before you apply

Applying takes about a minute. These four things decide how fast it moves after that.

Your profile is current

It's what we read first. Occupations, seniority and locations matter more than a long history.

Two examples you can talk through

Not a portfolio — just two pieces of work where you can explain the decisions and what you'd change.

A number in mind

What you're on now and what would make you move. We negotiate better when we know both.

Your notice period

Employers plan around it, and it's the question that stalls offers most often.

Once you apply, someone reads it and calls you before anything reaches the employer — usually within two working days.

More like this