Description:

Responsibilities:

-Work cross functionally with product managers, data scientists and product engineers, and communicate results to peers and leaders
.Develop scalable algorithms and methods to provide real-time recommendations
.Explore new technology shifts to determine how they might connect with the customer benefits we wish to deliver
.Work with engineering teams to implement new models while considering functionality for recommendation output
.Collaborate with Data Scientists to prototype new algorithms and design experiments for evaluation to enhance our marketing efficiency
.Contribute to a culture of continuous improvement, and data driven results
.Work with data scientists to create and refine features from the underlying data and build pipelines to train and deploy models
.Run regular A/B tests, gather data, perform statistical analysis, draw conclusions on the impact of your models
.Discover data sources, ingest and cleanse them in a meaningful way for data processing
.Participate in design discussions about new features and approaches to implementing new services
.Take end to end ownership of Machine Learning systems from data pipelines and training to real-time prediction engines
.Partner with data scientists to understand, implement, refine and design machine learning and other algorithms

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Requirement

s:Bachelors degree or higher (completed and verified prior to start) from an accredited universit
y.Preferably working experience in FinTech or Credit Card industr
y.Knowledgeable with Data Science tools and frameworks (i.e. Python, Scikit, NLTK, NumPy, Pandas, TensorFlow, Keras, R, Spark
);Software engineering fundamentals: version control systems (i.e. Git, GitHub) and workflows, and ability to write production-ready cod
e.Should have clear understanding of Generative AI and various LLM model
s.Databricks Delta Lake architecture and MLflow is an added advantag
e.Good knowledge of Azure/GCP cloud infrastructur
e.Strong knowledge of machine learning techniques (i.e. classification, regression, and clustering
);BS, MS, or PhD degree in Computer Science or related field, or equivalent practical experienc
e.Understand machine learning principles (training, validation, etc
.)Expertise in visualizing and manipulating big datase
tsKnowledge of data query and data processing tools (i.e. SQL

AI/ML Engineer