What data and statistics skills are currently in high demand and where are they in high demand? I have a job doing data analysis in finance. My current job is such that I don't have much exposure to things happening in the rest of my industry or other industries. I have a fair amount of knowledge about Bayesian statistics. 
I'd like to keep myself marketable, so I am curious what data and statistics skills are currently in high demand and where. The software world is awash in data, so I would expect them to need statisticians really badly, but my impression is that they are not in high demand.
A friend of mine has suggested that the software industry primarily needs "big data" skills, not statistics skills per se. 
What data and statistics skills are currently in high demand and where are they in high demand?
 A: 
A friend of mine has suggested that the software industry primarily
  needs "big data" skills, not statistics skills per se.

While partially agreeing with your friend's comment, I would like to point out that in any industry, Big data tools are opted, only if all the V's are satisfied.
I work as the head of data science at a leading customer support company. Here, I do data hacking both for the product and also for the growth of the company.
I primarily use time series analysis techniques for churn prediction and sales analysis. This also includes the behavioural analysis of the customers, competition and the industry.
On the product side, we use a range of techniques starting from sentiment analysis using LSTM's, recommendation algorithms, etc.
But the core focus lies on time series analysis. The general workflow would be: 


*

*Cleaning and moulding the data.

*the exploratory and explanatory analyses which involves identification of seasonality, trends and cycles. So, one need to explore correlations, auto-correlations, and several univariate and bivariate statistics; along with extensive plotting including the scatter, AFC, PAFC curves.

*Now comes the forecasting part, where various models are tested each other, taking the step - 2 into serious consideration.


Tools used by me: R, Python and Excel sometimes.
And even the blend of data science and growth hacking have proven to do magic in the domain of marketing. So, the demand for statisticians and math nerds would remain as is; and is not going to decline anywhere in the near future; especially when customer focused startups are blossoming across the world.
A: One unexpected place where these skills are in high demand: HR.  I ended up in the HR dept for a forward thinking tech company by chance after getting a masters in applied math.  Turns out a lot of companies are just becoming interested in how statistics and data analysis can help them.  Because HR analytics are in their relative infancy compared to well-explored areas like finance, this often involves relatively basic stuff like significance testing and OLS regression.  Right now I'm working on a predictive employee attrition model using Cox proportional hazards.  The field is on the upswing and there's a ton of opportunity to make a meaningful impact on significant problems while exercising a certain degree of creative license.  HR is also a great place to learn about how companies are structured as well as how to build your career.
