At Schwab, you’re empowered to make an impact on your career. Here, innovative thought meets creative problem solving, helping us “challenge the status quo” and transform the finance industry together.
Are you all about using data to provide customers better products and grow business? We are looking for qualified candidates to craft and implement scalable machine learning solutions for multifaceted financial products, deliver business insights from unstructured data with clear narratives and creative visualizations, and partner closely with the data infrastructure and platforms teams to develop tools and automation. We have a large and diverse set of data, sourced from our extensive client base and huge volume of transactions across multiple channels. This is a phenomenal opportunity to apply your craft as a data scientist while working with business partners to drive data-driven solutions.
Data, Analytics and Insights (DAI) is a hard-working, fun team of 140+ that supports multiple business units across Schwab with quantitative-based decision support. Our mission is to help our business partners better understand the needs and behaviors of our prospects and clients through analytics, data science, market research, and business intelligence.
You will work collaboratively with a team of product managers, data scientists, IA ops, and engineers, throughout the project lifecycle including data extraction and preparation, design and implementation of algorithms, and creating solutions that solve real world problems.
- Use NLP to build chatbot that will be used by Schwab clients and prospects across different channels and instrument Dialogflow for intents
- Experiment with LLMs and apply understanding in the evolving field of Generative AI
- Get hands-on with large disparate datasets, hack through complex and messy data, and analyze it using the latest algorithms and innovative techniques and tools.
- Use open source tools and platforms like Anaconda Enterprise & Python to apply algorithms and analytic models to big data problems.
NLP: Knowledge of NLP concepts including Generative AI, and hands on experience in building NLP models and experimenting with LLMs. Ability to make data driven decisions to train and re-train Dialogflow intents. Experience with extracting relevant data from user transcripts including cleaning, lemmatizing and building text corpus for developing models
Statistical Methodology: Knowledge of sophisticated techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc). Ability to understand model performance
Machine Learning: Knowledge of and experience with designing and implementing algorithms (clustering, decision tree learning, GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc), and the ability to articulate their real-world advantages and drawbacks.
Business insight: You understand the bigger picture for customers and the business and know how to probe beyond partners’ stated requests to really understand their needs and the value of information.
Graduate degree in Statistics, Mathematics, Computer Science, Operations Research, Engineering or similar quantitative field.- Hands on experience in working on platforms/environments such as Google Dialogflow, GCP, Tableau, SQL server, Hive
- 6+ years’ experience in delivering data science solutions/services
- 3+ years experience in Python, data engineering, analytics role
- Proactive, critical thinker, bias to action and a go-getter demeanor
Even Better.
- Enthusiastic quick learner who loves to code
- Experience in financial services would be a plus but not necessarily a requirement.