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 advantages 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
.
Requirement
- s: Bachelor’s degree or higher (completed and verified prior to start) from an accredited universit
- y. Preferably working experience in Fin Tech or Credit Card industr
- y. Knowledgeable with Data Science tools and frameworks (i.e. Python, Scikit, NLTK, Num Py, Pandas, Tensor Flow, Keras, R, Spark
- ); Software engineering fundamentals: version control systems (i.e. Git, Git Hub) 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/GC