USPBA Data Scientist C12

Our client operates in the Financial sector, with its headquarters rooted strongly in the United States. It has its branches spread to more than 160 countries, providing employment to more than 200k people all over the world. They fall in the Top 15 largest Banks in the United States. Its core business is to provide various Banking and Financial services to its clients. It is known to have one of the biggest balance sheet banks in the world (among others) aiding it to offer 360-degree financial services to its clients.

Role Description:

• The North America Consumer Bank Next Gen Analytics team analyzes millions of prospects and billions of customer level transactions using big data tools and machine learning, AI techniques to unlock opportunities for our clients in meeting their financial needs and create economic value for the bank.
• The team extracts relevant insights, identifies business opportunities, converts business problems into modeling framework, uses big data tools, latest deep learning, and machine learning algorithms to build predictive models, implement solutions and design go-to-market strategies for a huge variety of business problems

Responsibilities:

• Create best in class solutions – Design and implement stable best in class solutions using the recommended tools. Prove and improve the performance of the solution.
• Communication skills – Ability to extract and understand business need from partners.
• Translate and articulate technical design and performance to a senior business audience
• Strategic acumen – Should possess ability to see the big picture of business, identify and understand emerging trends, challenge status quo and design goals for growth
• Modeling and Tech Savvy – As an SME, stay current with the latest use cases of modeling community, machine learning algorithms, deep learning algorithms, public data sets and share knowledge within the larger team.
• Statistical mind set – Proficiency in basic statistics, hypothesis testing, segmentation, and predictive modeling.

Requirements:

• Masters with 6+ years of professional experience in fields that include but not exhaustive – Computer Science, Machine Learning, Operations Research, Econometrics, Statistics or in a highly quantitative field
• Hands-on experience in applied machine learning and Big Data. Good knowledge of scripting languages e.g., Python and libraries e.g., Keras, DEAP, NLTK, BERT, TensorFlow, CausalML, XGB, SKLEARN etc.
• Strong expertise in deep learning & machine learning algorithms, data analysis, pattern recognition.
• Structured thought process to identify, clearly articulate and solve complex problems and present them to the management in a structured and simpler form
• Excellent documentation skills (design documents, methods, internal wiki).