Senior Manager, Data Scientist

Job Description

Your Opportunity

Love using statistics to create insightful models, measure the effect of marketing activities, and make an impact on the quality of business decisions? Then we want you!

This is a great opportunity to apply your craft as a statistician/data scientist while working closely with business partners to deliver data-driven solutions.

We are looking for qualified candidates to design, build, and implement marketing mix models to guide marketing investment decisions. You will apply your statistical talent to develop quantitative models to measure and optimize cross channel marketing and promotional spending decisions.

Our large client base and multi-channel transaction volume offers a fertile data environment to uncover new insights and answers to key business questions. Our dynamic business generates many questions that provide lots of opportunity to get deep in data and have real impact.

Analytics and Business Insight (ABI) is a smart, fun team of 140+ that provide quantitative decision support to multiple business units across Schwab. We help our business partners better understand the needs and behaviors of our prospects and clients through analytics, data science, market research, and business intelligence.

What you’re good at

You will work collaboratively with marketing partners, analysts, and data engineers to develop and automate marketing mix optimization solutions. You’ll use your analytic, modeling, and consultation skills to help marketing leaders better understand what worked and guide them in making the best spending decisions going forward. This role will require technical sophistication, marketing knowledge, and hands on expertise to create actionable solutions to solve real-world marketing problems.

This role supports multiple marketing units across the Schwab enterprise.

• Work with marketing and analytic partners to quantify the impact of marketing investment decisions
• Get hands-on with big data to analyze time series leveraging the latest platforms, statistical modeling and optimization techniques
• Formulate panel based time-series regression models using hierarchical Bayesian modeling techniques
• Design, conduct, and analyze experiments to quantify the impact of marketing treatments
• Analyze observational data to quantify the effect of promotional events and offers
• Leverage tools and platforms like Anaconda Enterprise, Python, R and SAS to apply algorithms and analytic models to big and small data problems
• Formulate fixed or mixed effect regression model specifications
• Build regression models under a panel-based hierarchical Bayesian framework

What you bring

• Experience with conducting due-to and sensitivity analysis
• Explain your insights to a non-technical audience
• Creatively think of original solutions for the real world
• Thought leadership in using marketing mix models to improve marketing decisions
• Experience in solving complex marketing problems using quantitative models

Even better

• Experience implementing STAN/MCMC R packages to estimate regression coefficients
• Experience implement optimization algorithms using non-linear techniques

Business acumen: Understanding how marketing and promotions grow acquisition and improve retention. Quickly grasp the big picture. Know how to probe beyond stakeholders’ stated requests to understand what is truly needed to capture and drive business value.

What you have

• B.S. degree in Statistics, Mathematics, Economics, Mathematics, Operations Research, or similar quantitative field
• • 5+ years’ of experience in statistical modeling and analytics
  • Expertise in R and SQL. Comfort in Python and SAS
  • Desire to learn all aspects of big data and analytics projects including scoping business requirements, wrangling data, approaching business problems with analytic rigor, developing reusable data products and visualizing data to surface insights that drive business value and impact.
  Even better
  • Enthusiastic quick learner who loves to model and code, has a solid statistical foundation and wants to expand their data science experience
  • Experience using statistics and machine learning to solve complex business problems
  • Experience in financial services is a plus but not a requirement