Job Description

Are you passionate about data science with a comprehensive understanding of analytical principles, tools, technologies, and the capability to convey insights to both executive and non-technical audiences? If so, this could be the ideal opportunity for you.


As an Analytics Solutions Analyst on the Instrumentation & Metrics (I&M) team, you are in integral part of the team that will be responsible for leveraging your expertise in data science to develop and maintain production grade models using various analytical techniques. You will provide ad-hoc analytics support to the Payments organization, transforming complex data into actionable insights. Additionally, you will guide the team on best practices and techniques in data science, ensuring the effective use of data to drive business decisions.

Job responsibilities:

Develop complex analytical models that provide a comprehensive view of the business by integrating data from multiple sources. Utilize advanced SQL, Alteryx, Tableau, and Python programming skills, along with expertise in multivariate statistics, quantitative modeling, and advanced analytical methods (e.g., supervised/unsupervised machine learning, time-series predictions, NLP, etc.). Conduct data discovery and analytics to extract insights that enhance existing financial products and support decision-making processes. Collaborate with product managers, data architects, software engineers, and business analysts to build a company-centric analytics product in a production environment. Demonstrate excellent understanding of business strategy and data science opportunities. Communicate complex data challenges and solutions to diverse audiences across various levels of the banking organization, including those unfamiliar with advanced machine learning techniques.

Required qualifications, capabilities and skills:

Bachelor's or Master's degree in statistics, mathematics, data science, or a related technical or quantitative field, with 3+ years of applied experience. Strong understanding of agile methodologies, statistics, and AI/ML engineering, with a proven track record of developing and deploying business-critical machine learning models in production. Proficiency in programming languages such as Python, and experience with machine learning frameworks, libraries, and APIs, including TensorFlow, PyTorch, Scikit-learn, etc. Ability to identify and address AI/ML challenges, implement optimizations, and fine-tune models for optimal performance. Basic knowledge of data system components to determine necessary controls. Excellent written and verbal communication skills to effectively convey technical concepts and results to both technical and business audiences.

Preferred qualifications, capabilities and skills:

Familiarity with the financial services industry. Background in NLP and advanced analytics. Knowledge of financial products and services, including trading, investment, and risk management. * Experience working with databricks/snowflake.