Overview
On Site
Full Time
Skills
Creative Problem Solving
Finance
Unstructured Data
Decision Support
Business Intelligence
Project Lifecycle Management
Data Extraction
FOCUS
Art
Budget
Open Source
R
SAS
Analytical Skill
Big Data
Collaboration
Algorithms
Gradient Boosting
Machine Learning (ML)
Data Mining
Generalized Linear Model
Regression Analysis
k-means clustering
Decision Trees
Natural Language Processing
Artificial Intelligence
Social Network Analysis
Articulate
Business Acumen
Mathematics
Computer Science
Physics
Operations Research
Data Science
Python
Data Engineering
Analytics
Software Engineering
Data Visualization
Time Series
Statistics
Marketing
Modeling
Optimization
Quick Learner
Google Cloud
Google Cloud Platform
Financial Services
Job Details
Your Opportunity
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.
We believe in the importance of in-office collaboration and fully intend for the selected candidate for this role to work on site in the specified location(s).
Are you all about leveraging data to provide customers better products and grow business? We are looking for qualified candidates to design and implement scalable machine learning solutions for dynamic financial products, deliver business insights from unstructured data with clear narratives and creative visualizations, and partner closely with the data infrastructure and platform 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 great opportunity to apply your craft as a data scientist while working directly with business partners to drive data-driven solutions.
Schwab's AI and Data Science team is a hard-working, fun team of 40+ that supports multiple business units across the firm 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 data science, analytics, and business intelligence.
What you'll do
The Data Scientist will work collaboratively with a team of data scientists, analytics leads, engineers, and product owners throughout a project lifecycle, including data extraction and preparation, feature engineering, model design and development and everything in between- this is a role that will requires hands on expertise to create value adding solutions that solve real business problems.
This role supports multiple business units across the Schwab enterprise with primary focus on Marketing Mix optimization modeling.
What you bring
Statistical Methodology: Knowledge of advanced techniques and concepts (regression, properties of distributions, time series analysis and modeling, statistical tests and proper usage, etc.)
Machine Learning: Knowledge of and experience with designing and implementing algorithms (Gradient Boosting Trees, GLM/Regression, Random Forest, Neural Networks, etc.), and the ability to articulate their real-world advantages and drawbacks
Data Mining & Machine Learning: 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.), and the ability to articulate their suitability for a given challenge
Business acumen: Understanding the bigger picture for customers and the business and the know how to probe beyond stakeholders' stated requests to understand what is truly needed to capture and drive business value
What you have
Required Qualifications:
Preferred Qualifications:
In addition to the salary range, this role is also eligible for bonus or incentive opportunities.
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.
We believe in the importance of in-office collaboration and fully intend for the selected candidate for this role to work on site in the specified location(s).
Are you all about leveraging data to provide customers better products and grow business? We are looking for qualified candidates to design and implement scalable machine learning solutions for dynamic financial products, deliver business insights from unstructured data with clear narratives and creative visualizations, and partner closely with the data infrastructure and platform 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 great opportunity to apply your craft as a data scientist while working directly with business partners to drive data-driven solutions.
Schwab's AI and Data Science team is a hard-working, fun team of 40+ that supports multiple business units across the firm 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 data science, analytics, and business intelligence.
What you'll do
The Data Scientist will work collaboratively with a team of data scientists, analytics leads, engineers, and product owners throughout a project lifecycle, including data extraction and preparation, feature engineering, model design and development and everything in between- this is a role that will requires hands on expertise to create value adding solutions that solve real business problems.
This role supports multiple business units across the Schwab enterprise with primary focus on Marketing Mix optimization modeling.
- Get hands-on with big data as you hack through complex and messy data, and analyze it leveraging the latest algorithms and state-of-the-art techniques and tools
- Develop marketing mix model to measure channel efficiency and optimize marketing budget allocation
- Use open-source tools and platforms like Anaconda Enterprise, Python, R and SAS to apply algorithms and analytic models to big data problems
- 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
What you bring
Statistical Methodology: Knowledge of advanced techniques and concepts (regression, properties of distributions, time series analysis and modeling, statistical tests and proper usage, etc.)
Machine Learning: Knowledge of and experience with designing and implementing algorithms (Gradient Boosting Trees, GLM/Regression, Random Forest, Neural Networks, etc.), and the ability to articulate their real-world advantages and drawbacks
Data Mining & Machine Learning: 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.), and the ability to articulate their suitability for a given challenge
Business acumen: Understanding the bigger picture for customers and the business and the know how to probe beyond stakeholders' stated requests to understand what is truly needed to capture and drive business value
What you have
Required Qualifications:
- Graduate degree in a quantitative field (eg. Statistics, Mathematics, Computer Science, Engineering, Physics, Operations Research, etc.)
- 2+ years' experience in delivering data science/analytics solutions
- 2+ years' experience in Python, data engineering, analytics role
- Software engineering and code versioning skills
- Data visualization experience
Preferred Qualifications:
- Proactive, critical thinker, bias to action and a go-getter attitude
- Experience with time series modeling
- Experience with Bayesian statistics and modeling
- Experience with marketing mix modeling techniques
- Experience with optimization techniques
- Enthusiastic quick learner who loves to code
- Experience with Dataiku/Google Cloud Product and Big Query
- Experience in financial services industry
In addition to the salary range, this role is also eligible for bonus or incentive opportunities.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.