Senior data scientist financial

Job Description

D2D: These Senior Data Scientists will be working at a large global hotel company. They will build models around causal modeling between different financial KPIs and how they impact each other, not just correlations but causation (Revenue is dependent on different things). Everything is from a time series lens (financial forecasting, causal inference, anomaly detection, outliers). They have a forecasting platform that they will work on, dozens of different of algorithms of time series pedictions). Fold those into the platform (AWS). Doing a lot of work for finance, that is the focus area. Someone who has built causal models for finance. Products exist that need to be advanced, coming into the deep end of the project.

• Want to know that they worked on something material, something real that is being used at production quality that has an impact.

• Working with senior executives for investor relations forecasting.

• What are they building forecasting models for? From scratch?

• How are they/what metrics are they using to evaluate the forecasting performance?

• What have you actually done that has gone to production, what did YOU do vs. what the team did, not a lot of people going into this domain.

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Skills and Requirements

• 7+ years of Data Science experience

• Causal Modeling and Time Series modeling for financial analysis

• Python coding/development

• AWS

• GitLab

• PhD core sciences, computer science, economics - LOCAL TO CHICAGO

• PhD economics or working with corporate finance (not hedge funds)

• Financial planning analysis

• Investor relations preparation (forecasting data for that). Nothing is analytics or isngihts, but predictive work for an alorthitmic product. Pure Algorithmic product developmentnt.

• Chicago preferred, 2 on site

• Someone who came from core science (Physics, Math) or software engineering first, those translate to some of the strongest data scientists.