# Testing time series

**MAKING THE LEAP**

**How to change careers and become a data scientist - one quant’s experience**

One quant shares her story of switching from energy trading to data science: the resources she used, the classes she took, her decision to move to the Bay Area, and her advice for handling tech culture shock.

- *fast.ai*

**EASY, BREEZY**

**Airflow and the Future of Data Engineering: A Q&A**

“[F]uture startups will be catapulted up the data maturity curve with access to better, cheaper, more accessible analytics software and services.” - *Astronomer*

**HERE’S THE PROOF**

**Mathematicians becoming data scientists: Should you? How to?**

Tips for determining if you’ll actually like the work data scientists do and positioning your mathematics background as an asset when you’re interviewing. - *Quomodocumque*

**TICK TOCK**

**What’s Wrong With My Time Series**

When you want to test a model’s predictive power, cross validation is usually the way to go. However, since data points in a time series are dependent on each other, randomly selecting subsets for training and testing won’t do. Check out these other ways to determine error sources in time series. - *MultiThreaded*

**JOB REQ**

**Hiring a data scientist**

Hiring for a data analyst is no easy task. Wikimedia shares how they drew on existing resources to synthesize a better approach to interviewing and hiring a new member of their data team. - *Wikimedia*

### New from Mode

**4 Handy SQL Tips for Pivot Tables**

Best practices for cleaning and structuring data sets to work optimally with Mode pivot tables.

**Product updates:**