At Schwab, the business problem is to leverage data to provide customers with better products and grow the business by designing and implementing scalable machine learning solutions for dynamic financial products, delivering business insights from unstructured data, and partnering with data infrastructure and platform teams to develop tools and automation.
Requirements
- Knowledge of advanced techniques and concepts (regression, properties of distributions, time series analysis and modeling, statistical tests and proper usage, etc.)
- Knowledge of and experience with designing and implementing algorithms (Gradient Boosting Trees, GLM/Regression, Random Forest, Neural Networks, etc.)
- Knowledge and experience in advanced data mining & modeling techniques (GLM/Regression, K-Means Clustering, Decision Trees, Random Forest, GNBC, NLP, AI, Social Network Analysis, etc.)
- Python programming skills
- Data engineering skills
- Analytics skills
- Software engineering and code versioning skills
- Data visualization experience
Responsibilities
- Getting hands-on with large datasets as you hack through complex and messy data, analyze it leveraging the latest AI & Machine learning algorithms and tools.
- Use state of the art data science tools and packages like Python (Pandas, NumPy, Scikit-learn, etc.), SQL, data visualization tools (Matplotlib, Seaborn, Tableau/Power BI), familiarity with machine learning libraries (TensorFlow, PyTorch) and cloud platforms (GCP).
- Develop automated and algorithmic approaches to analyzing data and powering data products and predictions
- Work closely with business stakeholders to understand their needs, articulate how data science can help achieve objectives, and deliver regular updates
- Collaborate with Data Science Engineers to operationalize models
- Design and implement scalable machine learning solutions for dynamic financial products
- Deliver business insights from unstructured data with clear narratives and creative visualizations
Other
- Graduate degree in a quantitative field (eg. Statistics, Mathematics, Computer Science, Engineering, Physics, Operations Research, etc.)
- 1+ years’ experience in delivering data science/analytics solutions
- 1+ years’ experience in Python, data engineering, analytics role
- Proactive, critical thinker, bias to action and a go-getter attitude
- Enthusiastic quick learner who loves to code
