<p>Your Opportunity</p> <p>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.</p> <p>As a Sr. Manager (AI & Data Science) you will be part of the Product Modeling team within the Treasury & Capital Markets department. The Product Modeling team is responsible for developing data-driven analytics, forecasting, pricing and segmentation models, and generating forecasts on a recurring cadence across deposits, margins and other on-/off-balance sheet products.</p> <p>This role is a research role that is primarily focused on developing new models and enhancing existing models in that space. This position therefore requires a proven track record of publishing quantitative research (e.g. dissertation, peer-reviewed academic papers).</p> <p>To succeed in this role, you should:</p> <ul> <li>Possess solid programming and data manipulation skills, allowing you to extract valuable insights from large datasets and to write production-level code under a rigorous change management process; </li><li>Be well-versed in different statistic modeling techniques as well as machine learning models, and in building fundamental quantitative models from the ground up - enabling you to condense your observations into robust models; and </li><li>Be an excellent team player and a trusted advisor collaborating with other team members as well as be ready to present your results and observations to a wide group of stakeholders. </li></ul> <p>If you are looking for a role where you can leverage all your technical skills while having a direct business impact and want to be part of a very impactful and driven team within the Treasury organization, we encourage you to apply.</p> <p>What you have:</p> <p>What you have</p> <p>Required skills</p> <ul> <li>Ph.D. with a strong quantitative component (Applied Math, Statistics, Engineering, Economics, Physics, Financial Engineering). </li><li>Proven track record of publishing quantitative research. </li><li>At least 5 years of work experience, preferably in a large financial company, as a quantitative modeler working with large and complex datasets, with consideration given for post-graduate research. </li><li>Ability to develop new models, improve efficacy of existing models and rigorously test them. </li><li>Solid understanding of statistical and quantitative modeling concepts and practical experience using statistical techniques to extract insights from large datasets. </li><li>Solid theoretical understanding and hands-on experience in developing, deploying and maintaining supervised machine learning models. </li><li>Strong programming skills in a modern programming language (e.g., Python, C++) and familiarity with object-oriented coding principle. </li><li>Experience with a modern software change management process. </li><li>Advanced experience in extracting data from relational databases (e.g., via SQL). </li><li>Experience in visualizing data analytics and model results. </li><li>Strong work ethic, high self-motivation, proactive approach, attention to detail and ability to deliver under tight deadlines. </li><li>Excellent communication skills, both verbally and written. </li><li>Strong inter-personal skills and a collaborative team-player. </li></ul> <p>Preferred skills</p> <ul> <li>Prior work experience in a Treasury department of a large financial firm. </li><li>Prior experience modeling deposits, margin, and other balance sheet products. </li><li>Prior experience in developing unsupervised machine learning models. </li><li>Prior experience in developing deep learning models. </li></ul> <p>What you'll do:</p> <ul> <li>Gain a deep understanding of the various forecasting models which measure the market risk in financial projections associated with a diverse set of products across the balance sheet. </li><li>Analyze large datasets to extract insights into Schwab's balance sheet and clients, and to provide analytical support for strategic decisions. </li><li>Develop new models for margin and deposit products. This includes research, writing of model white papers and technical papers and model maintenance. </li><li>Familiarity with a modern software change management process. </li><li>Apply ML models to granular and rich datasets to improve forecasts and identify customer segments. </li><li>Leverages industry opportunities to expand the organization's capabilities in data science, engineering, and modeling techniques. </li></ul> <p>In addition to the salary range, this role is also eligible for bonus or incentive opportunities.</p>