Jobs in Analytics

Some job openings from WPS/Analytic Searches.com

Please review WPS searches below and contact me if you would like to have a confidential conversation.

Full position descriptions at http://www.analyticsearches.com/wps-search-current-positions/ .

Submit resume/ questions to mary@analyticsearches.com.

All referrals are appreciated and earn you $1000.00 each when hired.
—————————————————————————————-
Associate Analytics & Research/Connecticut
Bank Business Analyst/IL/To $95K
Bank Manager/Model Dev & Risk Mgt/IL/To $140K
Banking Risk Analyst/IL/To $100K
Credit Card Risk Analyst/ Illinois
Director, Analytics/Chicago/To $130K
Director of Analytics/NJ/To $140K
Quantitative Manager Advanced Analytics/DC/To $150K
Quantitative Modeler/DC/To $130K
Research Statistician/IL/To $110K
Senior Manager Data & Analytics/NY, IL/To $110K
Statistician/San Diego
VP Actuary Pricing/Connecticut
VP Digital Strategist/Chicago/To $150K
VP Enterprise Catastrophe Strategy and Reporting/CT
VP Strategy & Analytics/Chicago/To $150K

Submit resume or questions to mary@analyticsearches.com.

http://www.analyticsearches.com

Jill Dyche on 2012

In part 3 of the series for predictions for 2012, here is Jill Dyche, Baseline Consulting/DataFlux.

Part 2 was Timo Elliot, SAP at http://www.decisionstats.com/timo-elliott-on-2012/ and Part 1 was Jim Kobielus, Forrester at http://www.decisionstats.com/jim-kobielus-on-2012/

Ajay: What are the top trends you saw happening in 2011?

 

Well, I hate to say I saw them coming, but I did. A lot of managers committed some pretty predictable mistakes in 2011. Here are a few we witnessed in 2011 live and up close:

 

1.       In the spirit of “size matters,” data warehouse teams continued to trumpet the volumes of stored data on their enterprise data warehouses. But a peek under the covers of these warehouses reveals that the data isn’t integrated. Essentially this means a variety of heterogeneous virtual data marts co-located on a single server. Neat. Big. Maybe even worthy of a magazine article about how many petabytes you’ve got. But it’s not efficient, and hardly the example of data standardization and re-use that everyone expects from analytical platforms these days.

 

2.       Development teams still didn’t factor data integration and provisioning into their project plans in 2011. So we saw multiple projects spawn duplicate efforts around data profiling, cleansing, and standardization, not to mention conflicting policies and business rules for the same information. Bummer, since IT managers should know better by now. The problem is that no one owns the problem. Which brings me to the next mistake…

 

3.       No one’s accountable for data governance. Yeah, there’s a council. And they meet. And they talk. Sometimes there’s lunch. And then nothing happens because no one’s really rewarded—or penalized for that matter—on data quality improvements or new policies. And so the reports spewing from the data mart are still fraught and no one trusts the resulting decisions.

 

But all is not lost since we’re seeing some encouraging signs already in 2012. And yes, I’d classify some of them as bona-fide trends.

 

Ajay: What are some of those trends?

 

Job descriptions for data stewards, data architects, Chief Data Officers, and other information-enabling roles are becoming crisper, and the KPIs for these roles are becoming more specific. Data management organizations are being divorced from specific lines of business and from IT, becoming specialty organizations—okay, COEs if you must—in their own rights. The value proposition for master data management now includes not just the reconciliation of heterogeneous data elements but the support of key business strategies. And C-level executives are holding the data people accountable for improving speed to market and driving down costs—not just delivering cleaner data. In short, data is becoming a business enabler. Which, I have to just say editorially, is better late than never!

 

Ajay: Anything surprise you, Jill?

 

I have to say that Obama mentioning data management in his State of the Union speech was an unexpected but pretty powerful endorsement of the importance of information in both the private and public sector.

 

I’m also sort of surprised that data governance isn’t being driven more frequently by the need for internal and external privacy policies. Our clients are constantly asking us about how to tightly-couple privacy policies into their applications and data sources. The need to protect PCI data and other highly-sensitive data elements has made executives twitchy. But they’re still not linking that need to data governance.

 

I should also mention that I’ve been impressed with the people who call me who’ve had their “aha!” moment and realize that data transcends analytic systems. It’s operational, it’s pervasive, and it’s dynamic. I figured this epiphany would happen in a few years once data quality tools became a commodity (they’re far from it). But it’s happening now. And that’s good for all types of businesses.

 

About-

Jill Dyché has written three books and numerous articles on the business value of information technology. She advises clients and executive teams on leveraging technology and information to enable strategic business initiatives. Last year her company Baseline Consulting was acquired by DataFlux Corporation, where she is currently Vice President of Thought Leadership. Find her blog posts on www.dataroundtable.com.

Timo Elliott on 2012

Continuing the DecisionStats series on  trends for 2012, Timo Elliott , Technology Evangelist  at SAP Business Objects, looks at the predictions he made in the beginning of  2011 and follows up with the things that surprised him in 2011, and what he foresees in 2012.

You can read last year’s predictions by Mr Elliott at http://www.decisionstats.com/brief-interview-timo-elliott/

Timo- Here are my comments on the “top three analytics trends” predictions I made last year:

(1) Analytics, reinvented. New DW techniques make it possible to do sub-second, interactive analytics directly against row-level operational data. Now BI processes and interfaces need to be rethought and redesigned to make best use of this — notably by blurring the distinctions between the “design” and “consumption” phases of BI.

I spent most of 2011 talking about this theme at various conferences: how existing BI technology israpidly becoming obsolete and how the changes are akin to the move from film to digital photography. Technology that has been around for many years (in-memory, column stores, datawarehouse appliances, etc.) came together to create exciting new opportunities and even generally-skeptical industry analysts put out press releases such as “Gartner Says Data Warehousing Reaching Its Most Significant Inflection Point Since Its Inception.” Some of the smaller BI vendors had been pushing in-memory analytics for years, but the general market started paying more attention when megavendors like SAP started painting a long-term vision of in-memory becoming a core platform for applications, not just analytics. Database leader Oracle was forced to upgrade their in-memory messaging from “It’s a complete fantasy” to “we have that too”.

(2) Corporate and personal BI come together. The ability to mix corporate and personal data for quick, pragmatic analysis is a common business need. The typical solution to the problem — extracting and combining the data into a local data store (either Excel or a departmental data mart) — pleases users, but introduces duplication and extra costs and makes a mockery of information governance. 2011 will see the rise of systems that let individuals and departments load their data into personal spaces in the corporate environment, allowing pragmatic analytic flexibility without compromising security and governance.

The number of departmental “data discovery” initiatives continued to rise through 2011, but new tools do make it easier for business people to upload and manipulate their own information while using the corporate standards. 2012 will see more development of “enterprise data discovery” interfaces for casual users.

(3) The next generation of business applications. Where are the business applications designed to support what people really do all day, such as implementing this year’s strategy, launching new products, or acquiring another company? 2011 will see the first prototypes of people-focused, flexible, information-centric, and collaborative applications, bringing together the best of business intelligence, “enterprise 2.0”, and existing operational applications.

2011 saw the rise of sophisticated, user-centric mobile applications that combine data from corporate systems with GPS mapping and the ability to “take action”, such as mobile medical analytics for doctors or mobile beauty advisor applications, and collaborative BI started becoming a standard part of enterprise platforms.

And one that should happen, but probably won’t: (4) Intelligence = Information + PEOPLE. Successful analytics isn’t about technology — it’s about people, process, and culture. The biggest trend in 2011 should be organizations spending the majority of their efforts on user adoption rather than technical implementation.

Unsurprisingly, there was still high demand for presentations on why BI projects fail and how to implement BI competency centers.  The new architectures probably resulted in even more emphasis on technology than ever, while business peoples’ expectations skyrocketed, fueled by advances in the consumer world. The result was probably even more dissatisfaction in the past, but the benefits of the new architectures should start becoming clearer during 2012.

What surprised me the most:

The rapid rise of Hadoop / NoSQL. The potentials of the technology have always been impressive, but I was surprised just how quickly these technology has been used to address real-life business problems (beyond the “big web” vendors where it originated), and how quickly it is becoming part of mainstream enterprise analytic architectures (e.g. Sybase IQ 15.4 includes native MapReduce APIs, Hadoop integration and federation, etc.)

Prediction for 2012:

As I sat down to gather my thoughts about BI in 2012, I quickly came up with the same long laundry list of BI topics as everybody else: in-memory, mobile, predictive, social, collaborative decision-making, data discovery, real-time, etc. etc.  All of these things are clearly important, and where going to continue to see great improvements this year. But I think that the real “next big thing” in BI is what I’m seeing when I talk to customers: they’re using these new opportunities not only to “improve analytics” but also fundamentally rethink some of their key business processes.

Instead of analytics being something that is used to monitor and eventually improve a business process, analytics is becoming a more fundamental part of the business process itself. One example is a large telco company that has transformed the way they attract customers. Instead of laboriously creating a range of rate plans, promoting them, and analyzing the results, they now use analytics to automatically create hundreds of more complex, personalized rate plans. They then throw them out into the market, monitor in real time, and quickly cull any that aren’t successful. It’s a way of doing business that would have been inconceivable in the past, and a lot more common in the future.

 

About

 

Timo Elliott

Timo Elliott is a 20-year veteran of SAP BusinessObjects, and has spent the last quarter-century working with customers around the world on information strategy.

He works closely with SAP research and innovation centers around the world to evangelize new technology prototypes.

His popular Business Analytics blog tracks innovation in analytics and social media, including topics such as augmented corporate reality, collaborative decision-making, and social network analysis.

His PowerPoint Twitter Tools lets presenters see and react to tweets in real time, embedded directly within their slides.

A popular and engaging speaker, Elliott presents regularly to IT and business audiences at international conferences, on subjects such as why BI projects fail and what to do about it, and the intersection of BI and enterprise 2.0.

Prior to Business Objects, Elliott was a computer consultant in Hong Kong and led analytics projects for Shell in New Zealand. He holds a first-class honors degree in Economics with Statistics from Bristol University, England

Timo can be contacted via Twitter at https://twitter.com/timoelliott

 Part 1 of this series was from James Kobielus, Forrestor at http://www.decisionstats.com/jim-kobielus-on-2012/

Agneepath Movie Review

When you try and make a remake of old Bollywood classic, you risk some stuff. Especially if the classic is the legendary Amitabh Bachchan’s   Agneepath that was both a commericial flop, a total hit at the awards and now a cult favorite (see http://en.wikipedia.org/wiki/Agneepath)

So what can Karans Johar/Malhotra, Sanjay Dutt and Hrithik Roshan do that hasnt been done.

Well they have made the intense violence mind-blowing catchy and deliciously pulpy, with its unique Bollywood sweet sour mango flavor. Sanjay Dutt rocks the screen in evil intensity, Hrithik emotes with his eyes (wisely deciding to underplay his Vijay Deenanath Chauhan , rather than the over the top original) and even the supporting actors from the veteran Rishi Kapoor, the demure Priyanka Chopra and host of characters make this an incredibly cool movie to buy tickets for. I am sure Quentin Tarantino would find the violence inspiring – and if you have not seen Bollywood movies yet, well this is sure as good a time to start.

See it- and atleast in Mumbai, India , the movies are off to a good start in 2012.

related-

and

Using SAS and R Together

Proc r

 I really liked this code snippet paper from JSS, enough to upload and embed it here. It shows using R from within Base SAS is quite easy, though Phil Rack, of Minequest gets credit for writing the earliest macros on that (in SAS language product WPS ) at http://www.minequest.com/Bridge2R.html .
I also liked Phil Holland’s paper on that at http://www.hollandnumerics.co.uk/pdf/SAS2R2SAS_paper.pdf
and Sam Croker’s paper on using Time Series in both SAS and R at
A great blog on using both languages together is
SAS and R: Data Management, Statistical Analysis, and Graphics
The earliest book on the topic of R being used by SAS users was by Bob Muenchen, of course at
R for SAS and SPSS Users (Statistics and Computing)

Of course you can refer to official SAS/IML documentation as well for using SAS and R -
Case Studies on using R and SAS together can be seen from here-

 multiple case studies, and in each a comparison of R and SAS, as well as ways of combining the two together. This included calling R from SAS, and using R to generate SAS code.

Most striking for me was the comparison of SAS with R in a live, corporate financial context, and the presentation of R as a viable, robust, industrial strength option, with some unique advantages, and admitted weaknesses.

I hope that Hong can present this again to the Sydney Users of R Forum (SURF)

His presentation slides can be found here.

but the last word goes to this document on doing graphs  from

http://biostat.mc.vanderbilt.edu/wiki/pub/Main/RafeDonahue/doingmore_currentversion.pdf

drawing a plot with SAS/Graph and then modify its defaults and make it better. Along the way I will discuss issues that will arise with how the code runs and how SAS works and whatnot.
Then we’ll start over and do the whole thing all over again with R.