Data Scientist

Are you interested in building capabilities that enable the organization with innovation, speed, agility, scalability, and efficiency? The Global Technology team takes great pride in our culture where digital transformation is built into our DNA! When you join our organization at a major financial institution, you’ll unlock an exciting and impactful career – all while growing your skills and advancing your profession at one of the world’s leading financial services institutions. As a Senior Data Scientist on Institutional Retirement Strategies, you will partner with a diverse team of Engineers, Economists, Computer Scientists, Mathematicians, Physicists, Statisticians, and Actuaries to mine industry-leading internal data and develop new analytics capabilities. The role requires a combination of analytical expertise, business acumen, strategic thinking, client relationship skills, problem-solving abilities, and a passion for business impact. This is an exciting opportunity to be part of a growing strategic initiative. You should bring excellent problem-solving, communication, teamwork skills, agile working methods, strong business insight, inclusive leadership, and a continuous learning mindset. Here is what you can expect in a typical day: Develop advanced data science solutions based on the portfolio assigned by the Lead Data Scientist, including data analysis, model development, training, and testing. Write production-level code and collaborate with machine learning engineers to deploy models into production. Research new methods, algorithms, modeling techniques, and data analytics approaches. Partner with data engineers to build data pipelines and with software engineers to integrate solutions with business platforms. The Skills and expertise you bring: Advanced degree (Masters or Ph.D.) in Mathematics, Statistics, Engineering, Econometrics, Physics, Computer Science, Actuarial Science, Data Science, or similar quantitative fields. Experience tackling complex problems requiring in-depth analysis and judgment within broad practices and policies. Ability to learn new skills proactively and seek challenges. Excellent problem-solving, communication, and collaboration skills. Applied experience with several of the following: Machine Learning: Understanding of theory and application, including training, testing, interpreting, and monitoring models. Generative AI & Natural Language Processing: Experience with text analysis, NLP, LLMs (like BERT), and Gen AI technologies such as RAG, LangChain, LangGraph, and vector databases. Statistics and Computing: Knowledge of multivariable calculus, linear algebra, differential equations, probability, statistics, programming methodologies, and cloud computing. Familiarity with statistical techniques like Bayesian methods, time series analysis, etc. Data Acquisition and Transformation: Experience with APIs, SQL, Python, and data visualization tools. Database Management: Understanding of database structures, schema design, and data environments, including cloud/AWS. Data Wrangling: Skills in preparing and processing large, structured, and unstructured datasets. AWS DevOps: Experience with the software development lifecycle in an AWS environment. Programming Languages: Python, SQL. All qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status.

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